[ { "id": "https://openalex.org/W7155204273", "doi": "10.2139/ssrn.6626997", "title": "How Drones can Complement Trucks for Last-mile Delivery under Aerial Congestion: A Continuum Approximation Study", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Yuhui Zhai", "Ruifeng She", "Yanfeng Ouyang" ], "first_author": "Yuhui Zhai", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Leverage (statistics)", "Routing (electronic design automation)", "Complement (music)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.6626997" }, { "id": "https://openalex.org/W7141489063", "doi": "10.1109/iceaai68945.2026.11442519", "title": "A Wind-Aware Path Planning Method for UAVs in Urban Environments", "year": 2026, "publication_date": "2026-01-16", "type": "conference-paper", "language": null, "authors": [ "Juanjuan Gao", "Xing Liu", "Yuchen Xia", "Shengxuan Shang", "Tianrui Pang", "Benyuan Yang" ], "first_author": "Juanjuan Gao", "venue": null, "publisher": null, "abstract": "With the widespread adoption of unmanned aerial vehicles (UAVs) in urban logistics and surveillance, path planning in complex environments has emerged as a prominent research focus. Urban building clusters not only constitute geometric obstacles but also induce complex turbulent wind fields, which critically impact UAV flight safety and energy efficiency. This paper proposes a novel path planning method integrating Computational Fluid Dynamics (CFD) simulation with Particle Swarm Optimization (PSO). The workflow comprises three key stages. Firstly, flow field simulation is conducted for an urban block featuring both continuous rows and L-shaped buildings using COMSOL Multiphysics software, based on the turbulence model. Subsequently, a kinematics constraint model is established, incorporating collision detection, curvature limits, and windresistance maneuvering capabilities. Finally, an objective function is constructed, primarily centered on flight time and augmented with penalty terms, for which the optimal flight trajectory is solved via the PSO algorithm. Experimental results demonstrate that the proposed algorithm effectively avoids both physical obstacles and hazardous wind zones, generating a feasible flight path that effectively balances safety and time efficiency.", "keywords": [ "Motion planning", "Path (computing)", "Key (lock)", "Urban planning", "Trajectory" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/iceaai68945.2026.11442519" }, { "id": "https://openalex.org/W7125946500", "doi": "10.1109/tccn.2026.3658754", "title": "GraC 2 Allocator: An RL-Based Hypergraph k -Cut and Coloring Approach to UAV-Assisted Last-Mile Urban Logistics", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": null, "authors": [ "Jingjing Wang", "Jiachi Yan", "Ziwei Yan", "Rou Wen", "Jingchun Wu", "Yakun Ren", "Tanren Liu", "Xianneng Zou", "Kai Lei" ], "first_author": "Jingjing Wang", "venue": "IEEE Transactions on Cognitive Communications and Networking", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Unmanned Aerial Vehicles (UAVs) have emerged as a promising solution for urban logistics due to their flexibility, cost-efficiency, and rapid responsiveness. However, the spatial and temporal heterogeneity of large-scale parcel orders, combined with the neglect of critical post-delivery steps such as UAV hovering, returning, and recipient confirmation, poses major challenges to coordinated task scheduling and hinder system scalability. To address these challenges, we propose GraC2Allocator, a comprehensive two-phase framework for UAV-assisted last-mile urban logistics network. It covers the full service chain from the city-level transit center, through courier stations, to parcel recipients. In Phase 1, Parcel-to-Station Allocation is formulated as a hypergraphk-cut problem and optimized via a reinforcement learning (RL) strategy enhanced by Graph Neural Networks (GNNs) and the multi-head attention mechanism, thereby minimizing inter-group cutting cost and enhancing the spatio-temporal coherence of parcel clusters. In Phase 2, Parcel-to-UAV Allocation is modeled as a pruning theory based dynamic graph coloring problem: 1) Edge reconfiguration guarantees an inter-task conflict-free scheduling result; 2) Lightweight recoloring achieves a near-100% task execution rate (TER), approaches the theoretical lower bound on the number of required UAVs (i.e., the smallest chromatic number), and reduces computation complexity. Extensive evaluations based on real-world logistics data from Hangzhou City demonstrate that the proposed GraC2Allocator framework achieves up to about 130% improvement in delivery efficiency, 60% reduction in UAV deployment, and 70% reduction in end-to-end transmission delay compared with baselines, thereby enabling highly efficient, scalable, and full-life-cycle on-demand delivery in dense urban environments.", "keywords": [ "Scheduling (production processes)", "Control reconfiguration", "Hypergraph", "Backhaul (telecommunications)", "Graph", "Pruning", "Reinforcement learning", "Motion planning", "Computation" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tccn.2026.3658754" }, { "id": "https://openalex.org/W3200556744", "doi": "10.1007/978-3-030-86433-0_9", "title": "A Feature Based Solution Approach for the Flying Sidekick Traveling Salesman Problem", "year": 2021, "publication_date": "2021-01-01", "type": "conference-paper", "language": "en", "authors": [ "Maurizio Boccia", "Andrea Mancuso", "Adriano Masone", "Claudio Sterle" ], "first_author": "Maurizio Boccia", "venue": "Communications in computer and information science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Solver", "Computer science", "Drone", "Travelling salesman problem", "Vehicle routing problem", "A priori and a posteriori", "Truck", "Operations research", "Routing (electronic design automation)", "Feature (linguistics)", "Problem solver", "Computer network" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-030-86433-0_9" }, { "id": "https://openalex.org/W4388885659", "doi": "10.22214/ijraset.2023.56559", "title": "Automated Drone Delivery System", "year": 2023, "publication_date": "2023-11-21", "type": "article", "language": "en", "authors": [ "Prof. U. M. Bansode", "Prasanna Kulkarni", "Yogesh Kedar", "Onkar Saravde", "Kaushal Nikam" ], "first_author": "Prof. U. M. Bansode", "venue": "International Journal for Research in Applied Science and Engineering Technology", "publisher": "International Journal for Research in Applied Science and Engineering Technology (IJRASET)", "abstract": "Abstract: In the realm of urban logistics, the deployment of automated drone delivery systems has emerged as a transformative solution for urgent package deliveries. This research endeavors to design and construct a fully autonomous drone tailored for rapid and precise deliveries from scratch. Leveraging innovative technologies, including Arduino Uno as the central processing unit, along with GPS modules, NRF24LO1, Ultrasonic sensors, and advanced artificial intelligence algorithms, we create a sophisticated delivery system. Central to our approach is the strategic placement of multiple delivery stations across the city. Each drone is dedicated to a specific route between two delivery stations. When a delivery order is placed, the drone's software autonomously calculates the optimal distance to the nearest delivery station, ensuring swift and energy-efficient deliveries. Crucially, our system operates without human intervention, relying solely on advanced artificial intelligence algorithms to navigate the urban landscape effectively. This paper elucidates the technical intricacies of our drone's design, detailing the integration of sensors, software algorithms, and communication modules. Through rigorous experimentation and analysis, we validate the efficacy of our automated drone delivery system. Our findings not only showcase the practicality of autonomous drone technology in urban logistics but also underscore the potential for its widespread implementation in real-world scenarios, revolutionizing the future of package deliveries.", "keywords": [ "Drone", "Computer science", "Software deployment", "Software", "Systems engineering", "Arduino", "Construct (python library)", "Software engineering", "Embedded system", "Engineering", "Operating system" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.22214/ijraset.2023.56559" }, { "id": "https://openalex.org/W7115698050", "doi": "10.5281/zenodo.17947355", "title": "Global Light Delivery Drone Market Overview: How Autonomous Aerial Logistics Are Redefining Last-Mile Delivery", "year": 2025, "publication_date": "2025-12-16", "type": "report", "language": null, "authors": [ "next move strategy consulting" ], "first_author": "next move strategy consulting", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "The global light delivery drone market is undergoing rapid transformation as industries seek faster, cost-efficient, and flexible delivery solutions. Valued at USD 1.6 billion in 2023, the market is projected to reach USD 23.7 billion by 2030, expanding at a compound annual growth rate of 42.7% from 2024 to 2030. Light delivery drones are unmanned aerial vehicles designed to transport small parcels such as consumer goods, food, medical supplies, and mail over short to medium distances. Their ability to operate autonomously, reach remote locations, and significantly reduce delivery time positions them as a disruptive force in logistics, healthcare, retail, and emergency response. This manuscript analyzes the market definition, growth drivers, technological trends, segmentation, regional dynamics, and competitive landscape shaping the evolution of the global light delivery drone market", "keywords": [ "Drone", "Market share", "Delivery system", "Market manipulation", "Annual growth %", "Market segmentation" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.17947355" }, { "id": "https://openalex.org/W7152081339", "doi": "10.3390/vehicles8040085", "title": "Simulation-Driven Approach to Evaluate a Reinforcement Learning-Based Navigation System for Last-Mile Drone Logistics", "year": 2026, "publication_date": "2026-04-08", "type": "article", "language": "en", "authors": [ "Zakaria Benali", "Amina Hamoud" ], "first_author": "Zakaria Benali", "venue": "Vehicles", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Unmanned Aerial Systems (UAS) offer sustainable solutions for urban last-mile logistics, yet existing navigation algorithms struggle with the complexity of dynamic metropolitan environments. This study optimises a reinforcement learning (RL)-based guidance, navigation, and control (GNC) algorithm using a Proximal Policy Optimisation (PPO) model within a high-fidelity simulation of Bristol City Centre. The primary contribution is training the RL model to autonomously detect and avoid dynamic obstacles, specifically manned aircraft, to ensure safe and legal drone operations. Additionally, flight operations are continuously monitored via a Structured Query Language (SQL) database to verify compliance with low airspace regulations. Simulation results demonstrate that the proposed framework achieves high obstacle detection accuracy under nominal conditions, while the implementation of curriculum learning significantly enhances the system’s adaptability and recovery capabilities during high-speed, dynamic encounters.", "keywords": [ "Drone", "Reinforcement learning", "Adaptability", "Obstacle", "Obstacle avoidance", "Trajectory", "Control (management)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2624-8921/8/4/85/pdf?version=1775646624" }, { "id": "https://openalex.org/W7115684951", "doi": "10.5281/zenodo.17947356", "title": "Global Light Delivery Drone Market Overview: How Autonomous Aerial Logistics Are Redefining Last-Mile Delivery", "year": 2025, "publication_date": "2025-12-16", "type": "report", "language": null, "authors": [ "next move strategy consulting" ], "first_author": "next move strategy consulting", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "The global light delivery drone market is undergoing rapid transformation as industries seek faster, cost-efficient, and flexible delivery solutions. Valued at USD 1.6 billion in 2023, the market is projected to reach USD 23.7 billion by 2030, expanding at a compound annual growth rate of 42.7% from 2024 to 2030. Light delivery drones are unmanned aerial vehicles designed to transport small parcels such as consumer goods, food, medical supplies, and mail over short to medium distances. Their ability to operate autonomously, reach remote locations, and significantly reduce delivery time positions them as a disruptive force in logistics, healthcare, retail, and emergency response. This manuscript analyzes the market definition, growth drivers, technological trends, segmentation, regional dynamics, and competitive landscape shaping the evolution of the global light delivery drone market", "keywords": [ "Drone", "Market share", "Delivery system", "Market manipulation", "Annual growth %", "Market segmentation" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.17947356" }, { "id": "https://openalex.org/W7161201602", "doi": "10.1016/j.icte.2026.05.002", "title": "Optimizing UAV last-mile delivery with constraint-aware evolutionary computation", "year": 2026, "publication_date": "2026-05-01", "type": "article", "language": "en", "authors": [ "Pei-Fa Sun", "Sang-Woon Jeon" ], "first_author": "Pei-Fa Sun", "venue": "ICT Express", "publisher": "Elsevier BV", "abstract": "Unmanned aerial vehicles (UAVs) have demonstrated great potential for last-mile package delivery due to their accessibility, efficiency, cost-effectiveness, environmental advantages, and ability to provide contactless services. Nevertheless, significant challenges remain, including the avoidance of no-fly zones, the handling of fragile cargo, and strict motion constraints such as limits on speed, acceleration, and safe takeoff/landing requirements. To address these challenges, this paper proposes a last-mile delivery model (LMDM) that incorporates no-fly zone avoidance, fragile cargo protection, motion constraints, and energy consumption minimization into UAV trajectory planning. Since the LMDM is inherently non-convex and difficult to solve using conventional optimization methods, we employ evolutionary computation (EC) techniques, along with a constraint-handling mechanism designed to ensure feasibility while achieving energy-efficient UAV trajectories. Numerical evaluations demonstrate that the proposed constraint-handling method can efficiently produce feasible solutions that satisfy various constraints of last-mile delivery and reduce total energy consumption, whereas the conventional penalty function approach fails to find feasible ones.", "keywords": [ "Trajectory", "Computation", "Minification", "Energy consumption", "Evolutionary computation", "Penalty method", "Evolutionary algorithm", "Mechanism (biology)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.icte.2026.05.002" }, { "id": "https://openalex.org/W4417066762", "doi": "10.2139/ssrn.5871916", "title": "A Bi-Level Heuristic Approach for the Truck-Drone Last-Mile Delivery Problem with Dynamic PID Control", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": null, "authors": [ "Heictor Costa", "Fernando José Von Zuben" ], "first_author": "Heictor Costa", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Control theory (sociology)", "Heuristic", "Control (management)", "Control system", "PID controller", "Optimal control" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5871916" }, { "id": "https://openalex.org/W4404478103", "doi": "10.1007/978-3-031-74501-0_14", "title": "Parcel Delivery with Eco-Friendly Drone Technologies", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Gabriele Barrile", "Clemente Maesano", "Sonia Calluso", "Piero Francesco Spano’" ], "first_author": "Gabriele Barrile", "venue": "Lecture notes in networks and systems", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Drone", "Environmentally friendly", "Computer science", "Architectural engineering", "Engineering", "Biology", "Ecology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-74501-0_14" }, { "id": "https://openalex.org/W2911563202", "doi": null, "title": "Assessment of the possibility of adoption and impact of blockchain, IoT and Drones technology in the different types of last-mile delivery.", "year": 2018, "publication_date": "2018-04-11", "type": "article", "language": "en", "authors": [ "Martinez Padilla", "Carlos Eduardo" ], "first_author": "Martinez Padilla", "venue": null, "publisher": null, "abstract": "evaluate the possible impacts that new upcoming technologies, might have on the most important operative characteristics of last-mile, and with this relationship define which types of business will be more likely to adopt the studied technologies in the future.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Internet of Things", "Blockchain", "Business", "Computer security", "Marketing", "Computer science", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://webthesis.biblio.polito.it/7276/" }, { "id": "https://openalex.org/W4411612614", "doi": "10.1007/978-981-96-1687-9_8", "title": "Unlocking the Skies: Addressing the Role of Government Support and Policies in Fueling the Adoption of Drones in Last-Mile Deliveries", "year": 2025, "publication_date": "2025-01-01", "type": "conference-paper", "language": "en", "authors": [ "Kalya Lakshmi Sainath", "C. Lakshmi Devasena" ], "first_author": "Kalya Lakshmi Sainath", "venue": "Lecture notes in networks and systems", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Mile", "Drone", "Government (linguistics)", "Aeronautics", "Business", "Last mile (transportation)", "Public administration", "Political science", "Engineering", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-981-96-1687-9_8" }, { "id": "https://openalex.org/W7113318476", "doi": null, "title": "Critical factors characterizing consumers’ intentions to use drones for last-mile delivery: Does delivery risk matter?", "year": null, "publication_date": null, "type": "article", "language": null, "authors": [ "Osakwe, Christian Nedu", "Hudik, Marek", "Říha, David", "Stros, Michael", "Ramayah, T." ], "first_author": "Osakwe, Christian Nedu", "venue": "RePEc: Research Papers in Economics", "publisher": "Federal Reserve Bank of St. Louis", "abstract": "Uncrewed Aerial Vehicle (UAV), commonly known as a drone, has become popular in military and recreational circles. Although their usage in commerce is relatively low, a continuous rise in commercial use, especially for last-mile delivery, in the future is anticipated. Consequently, there is a necessity for a greater understanding of consumers' readiness to accept the latest technological application to increase knowledge, business, and managerial practice. Specifically, this study aims to investigate consumers’ intentions to deploy drones for last-mile delivery. The study applies the social cognitive theory and the model of goal-directed behaviour. It investigates the effect of outcome expectancy, lifestyle compatibility, perceived self-efficacy, consumer attitude, and the desire of usage for delivery drones among European millennial consumers. Additionally, it examines whether delivery risk moderates the influence of attitude and desire to use delivery drones. The authors discovered that the aforementioned are positively related to consumer attitude. Consumer attitude as such is positively associated with the desire and intention to use this method of delivery. Furthermore, the intention to use drone delivery is positively influenced by the desire for this delivery, outcome expectancy, and lifestyle compatibility. These findings indicate the importance of desire and lifestyle compatibility as predictors. At the theoretical level, the results support the perspective that social cognitive theory, together with the model of goal-directed behaviour, is an adequate framework to account for consumer intentions.", "keywords": [ "Drone", "Outcome (game theory)", "Recreation", "Risk perception", "Cognition", "Social cognitive theory", "Perspective (graphical)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://www.sciencedirect.com/science/article/pii/S0969698921004318" }, { "id": "https://openalex.org/W4410829345", "doi": "10.52783/jisem.v10i49s.10103", "title": "\"Scalable Truck-Drone Coordination with Reinforcement Learning: Toward Real-Time Last-Mile Delivery Optimization\"", "year": 2025, "publication_date": "2025-05-23", "type": "article", "language": "en", "authors": [ "Ali Abdul Razzaq Taresh" ], "first_author": "Ali Abdul Razzaq Taresh", "venue": "Journal of Information Systems Engineering & Management", "publisher": "Lectito Journals", "abstract": "The study offers a new reinforcement learning contour to adapt the traveling seller problem with a drone (TSP-D), which faces challenges in final delivery logistics. The proposed method benefits from a near proximal political adaptation (PPO) combined with a deep remaining forward nerve architecture to effectively coordinate truck-drainage operations. A large contribution lies in extended state representation, which integrates the position of transit, the remaining travel time and viable drone-causal nodes, which use the algorithm of Dijkstra. The model was evaluated under two scenarios: unlimited and limited drone area. The results show calculation performance on better routing efficiency, solution quality and benchmark algorithms. PPO ensures policy stability and effective learning in a complex urban environment. The residual architecture reduces the disappearance of the disappearance, which enables intensive network training. This approach supports scalable and intelligent decision -making for drone -assisted logistics. The study helps to promote real -time, data -driven distribution systems for final measurement.", "keywords": [ "Drone", "Truck", "Reinforcement learning", "Scalability", "Mile", "Last mile (transportation)", "Computer science", "Reinforcement", "Engineering", "Artificial intelligence", "Automotive engineering", "Operating system" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://jisem-journal.com/index.php/journal/article/download/10103/4643" }, { "id": "https://openalex.org/W4390875780", "doi": "10.3390/smartcities7010007", "title": "Using Explainable Artificial Intelligence (XAI) to Predict the Influence of Weather on the Thermal Soaring Capabilities of Sailplanes for Smart City Applications", "year": 2024, "publication_date": "2024-01-15", "type": "article", "language": "en", "authors": [ "Maren Schnieder" ], "first_author": "Maren Schnieder", "venue": "Smart Cities", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Background: Drones, also known as unmanned aerial vehicles, could potentially be a key part of future smart cities by aiding traffic management, infrastructure inspection and maybe even last mile delivery. This paper contributes to the research on managing a fleet of soaring aircraft by gaining an understanding of the influence of the weather on soaring capabilities. To do so, machine learning algorithms were trained on flight data, which was recorded in the UK over the past ten years at selected gliding clubs (i.e., sailplanes). Methods: A random forest regressor was trained to predict the flight duration and a random forest (RF) classifier was used to predict whether at least one flight on a given day managed to soar in thermals. SHAP (SHapley Additive exPlanations), a form of explainable artificial intelligence (AI), was used to understand the predictions given by the models. Results: The best RF have a mean absolute error of 5.7 min (flight duration) and an accuracy of 81.2% (probability of soaring in a thermal on a given day). The explanations derived from SHAP are in line with the common knowledge about the effect of weather systems to predict soaring potential. However, the key conclusion of this study is the importance of combining human knowledge with machine learning to devise a holistic explanation of a machine learning model and to avoid misinterpretations.", "keywords": [ "Random forest", "Soar", "Computer science", "Artificial intelligence", "Machine learning", "Meteorology", "Aeronautics", "Engineering", "Geography" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2624-6511/7/1/7/pdf?version=1705302290" }, { "id": "https://openalex.org/W4416545249", "doi": "10.15446/dyna.v92n239.120412", "title": "Mapping the evolution of drone-based last-mile delivery: a bibliometric analysis with field insights from Colombia", "year": 2025, "publication_date": "2025-11-11", "type": "article", "language": "en", "authors": [ "Luz Maribel Guevara-Ortega", "Juan Enrique Hidalgo-Urrea", "Luz Mireya Candil-Parra", "William Rafael Navarro-Zúñiga" ], "first_author": "Luz Maribel Guevara-Ortega", "venue": "DYNA", "publisher": "National University of Colombia", "abstract": "The article combines a bibliometric analysis of 301 studies (2019–2025) with a survey of 70 Colombian logistics leaders. It identifies an annual scientific growth rate of 14.96 %, with emerging emphasis on sustainability, optimized routes, and hybrid truck-drone fleets. Respondents report key barriers: air-space regulation (80 %), limited payload capacity (65.7 %), insufficient infrastructure (64.3 %), and concerns about security, privacy, and high up-front costs. Integrating both approaches, the authors propose an urban pilot inspired by Milan, tailored to the Colombian context, profitable even at 50 % utilization and yielding a return above 90 % in the first year. They conclude that last-mile drone adoption demands clear regulatory frameworks, infrastructure investment, and risk-management strategies to build trust among users and operators.", "keywords": [ "Payload (computing)", "Field (mathematics)", "Drone", "Key (lock)", "Bibliometrics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://revistas.unal.edu.co/index.php/dyna/article/download/120412/96105" }, { "id": "https://openalex.org/W7136324054", "doi": "10.1109/itsc60802.2025.11423255", "title": "Last-Mile Delivery Optimisation with Autonomous Vehicles and Drones for Trust-Aware Multimodal Medical Logistics in Urban Environments", "year": 2025, "publication_date": "2025-11-18", "type": "conference-paper", "language": "en", "authors": [ "Yanyu Long", "Safaa Sindi", "Stewart A. Birrell", "Seng W. Loke", "Bahareh Nakisa" ], "first_author": "Yanyu Long", "venue": null, "publisher": null, "abstract": "This study addresses last-mile urban medical logistics through a multimodal fleet of autonomous vehicles and drones, including autonomous vans and trucks. We propose an environment-aware optimisation framework for last-mile delivery optimisation that integrates trust quantification, adaptive algorithm selection, and real-time decision-making. The system models road and environmental conditions using multi-source data and selects path-planning strategies, such as Dijkstra, A* or Greedy Best-First Search, according to delivery urgency and context. A trust evaluation mechanism fuses subjective perceptions with objective performance to embed trust scores into the optimisation process. Machine-learning models predict delivery delays and guide vehicle scheduling under dynamic urban logistics network conditions. In simulations based on Coventry, UK; integrating trust metrics with environment-sensitive routing reduces mean delivery time by 28%, while delay-prediction error drops to ±3.04 s; drones deliver insulin 90% faster than trucks despite slightly lower trust scores (-1.6%). These findings underscore the value of incorporating socio-technical factors, especially trust in time-sensitive, safety-critical multimodal urban logistics.", "keywords": [ "Drone", "Key (lock)", "Action (physics)", "Public transport" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://pure.coventry.ac.uk/ws/files/119923519/Long2026AAM.pdf" }, { "id": "https://openalex.org/W7118008679", "doi": "10.1007/978-981-95-0603-3_23", "title": "Machine Learning Enabled UAV Route Optimization for Last-Mile Delivery", "year": 2026, "publication_date": "2026-01-01", "type": "conference-paper", "language": "en", "authors": [ "Vedagiri Sri Harsha", "K. Ratna Kumar" ], "first_author": "Vedagiri Sri Harsha", "venue": "Lecture notes on multidisciplinary industrial engineering", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Obstacle", "Work (physics)", "Artificial neural network", "Order (exchange)", "Smart city" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-981-95-0603-3_23" }, { "id": "https://openalex.org/W7172084804", "doi": null, "title": "E-commerce & last mile logistics", "year": 2026, "publication_date": "2026-06-28", "type": "dissertation", "language": "el", "authors": [ "Μαριάνθη Νεκταρία Λαδά" ], "first_author": "Μαριάνθη Νεκταρία Λαδά", "venue": "Dione (University of Piraeus)", "publisher": "University of Piraeus", "abstract": "Η ραγδαία ανάπτυξη του ηλεκτρονικού εμπορίου (e-commerce) έχει επιφέρει σημαντικές μεταβολές στη λειτουργία των εφοδιαστικών αλυσίδων και ιδιαίτερα στις αστικές εμπορευματικές μεταφορές. Η αυξανόμενη ζήτηση για γρήγορες, ευέλικτες και αξιόπιστες παραδόσεις έχει αναδείξει το τελευταίο στάδιο της διανομής, γνωστό ως last-mile delivery, σε έναν από τους σημαντικότερους και πιο απαιτητικούς τομείς των σύγχρονων logistics. Παράλληλα, η εντατικοποίηση των διανομών στις αστικές περιοχές δημιουργεί σημαντικές προκλήσεις που σχετίζονται με την κυκλοφοριακή συμφόρηση, την κατανάλωση ενέργειας, τις εκπομπές αερίων του θερμοκηπίου και τη συνολική περιβαλλοντική επιβάρυνση των πόλεων. Σκοπός της παρούσας εργασίας είναι η διερεύνηση της σχέσης μεταξύ του ηλεκτρονικού εμπορίου και των city logistics, με έμφαση στις επιπτώσεις που προκαλεί η ανάπτυξη του e-commerce στις αστικές διανομές και στη λειτουργία του last-mile delivery. Μέσα από εκτενή βιβλιογραφική ανασκόπηση εξετάζονται η εξέλιξη των city logistics, οι βασικές λειτουργίες και προκλήσεις τους, οι μεταβολές που επιφέρει το ηλεκτρονικό εμπόριο στις εφοδιαστικές αλυσίδες, καθώς και οι περιβαλλοντικές συνέπειες των αυξανόμενων αστικών μεταφορών. Επιπλέον, αναλύονται σύγχρονες λύσεις και καινοτομίες που αποσκοπούν στη βελτίωση της αποδοτικότητας και της βιωσιμότητας των αστικών logistics, όπως τα Urban Consolidation Centers (UCCs), οι ψηφιακές τεχνολογίες, τα αυτόνομα οχήματα και drones, τα ηλεκτρικά οχήματα, τα ποδήλατα μεταφοράς και τα εναλλακτικά μοντέλα παράδοσης. Τέλος, παρουσιάζεται η μελέτη περίπτωσης των Βρυξελλών, η οποία αναδεικνύει πρακτικές βιώσιμης αστικής εφοδιαστικής και παρέχει χρήσιμα συμπεράσματα για την αποτελεσματικότερη ενσωμάτωση των logistics στον σχεδιασμό των έξυπνων πόλεων. Τα ευρήματα της εργασίας καταδεικνύουν ότι η αξιοποίηση καινοτόμων τεχνολογιών, η συνεργασία δημόσιου και ιδιωτικού τομέα και η εφαρμογή βιώσιμων πολιτικών αποτελούν βασικές προϋποθέσεις για τη βελτίωση των συστημάτων last-mile delivery και τη μείωση των περιβαλλοντικών επιπτώσεων στις αστικές περιοχές.", "keywords": [ "City logistics", "Consolidation (business)", "Work (physics)", "Humanitarian Logistics", "Government (linguistics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dione.lib.unipi.gr/xmlui/bitstream/unipi/19657/3/" }, { "id": "https://openalex.org/W4226368408", "doi": "10.2139/ssrn.4084251", "title": "Ffp: A Force Field Protocol for the Tactical Management of Uav Conflicts", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Jamie Wubben", "Carlos T. Calafate", "Juan‐Carlos Cano", "Pietro Manzoni" ], "first_author": "Jamie Wubben", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Protocol (science)", "Field (mathematics)", "Aeronautics", "Computer security", "Engineering", "Computer science", "Medicine", "Mathematics" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4084251" }, { "id": "https://openalex.org/W4406025174", "doi": "10.2139/ssrn.5079937", "title": "Heuristic Evaluation in A-Star Algorithm for Enhanced Urban Uav Path Optimization", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": "en", "authors": [ "Hari Balakrishnan", "Abhilash Suryan", "Anu Plavara Alex", "Sonia S. Raj", "Guang Chun Zhang" ], "first_author": "Hari Balakrishnan", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Heuristic", "Path (computing)", "Star (game theory)", "A* search algorithm", "Computer science", "Mathematical optimization", "Algorithm", "Mathematics", "Artificial intelligence", "Computer network" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5079937" }, { "id": "https://openalex.org/W4415927802", "doi": "10.4018/979-8-3373-4952-7.ch006", "title": "Drone Taxis and Drone Deliveries in Smart Logistics Security Surveillance", "year": 2025, "publication_date": "2025-11-05", "type": "book-chapter", "language": "ng", "authors": [ "Nidhi Kastwar", "Aakash Gupta" ], "first_author": "Nidhi Kastwar", "venue": null, "publisher": null, "abstract": "Integrating drone taxis and drone-based delivery systems is reshaping the landscape of smart logistics worldwide. These surveillance and aerial technologies offer solutions for last-mile delivery, congestion mitigation, and real-time supply chain responsiveness. However, their adoption introduces complex regulatory, technological, ethical, and operational challenges. Effective governance frameworks are needed to address airspace management, liability, insurance, and cross-jurisdictional coordination issues in the context of security surveillance. Technological innovations must be balanced with robust cybersecurity and data protection measures. Ethical imperatives demand that privacy, environmental impact, and social equity be considered in deployment strategies. The chapter examines these dynamics, drawing on international developments and referencing India as a key case for regulatory experimentation. The analysis aims to provide actionable insights to stakeholders seeking to advance sustainable, efficient, and responsible adoption of drone technologies in smart logistics", "keywords": [ "Drone", "Taxis", "Software deployment", "Context (archaeology)", "Key (lock)", "Supply chain", "Corporate governance", "Smart city" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.4018/979-8-3373-4952-7.ch006" }, { "id": "https://openalex.org/W7104576663", "doi": "10.1109/tits.2025.3618724", "title": "Real-Time Enhancements of Digital Twins With Incremental Time Series Data in Networked Air-Ground Cooperative UAV Swarm Systems", "year": 2025, "publication_date": "2025-11-10", "type": "article", "language": null, "authors": [ "Mengjie Lee", "Yining Zhu", "Yujiao Hu", "Yan Pan", "Jinchao Chen", "Yuan Yao", "Gang Yang", "Xingshe Zhou" ], "first_author": "Mengjie Lee", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Unmanned Aerial Vehicles (UAVs) are emerging as a pivotal component in the field of intelligent transportation systems. Leveraging virtual-physical interactions, digital twin technology significantly enhances the adaptability of UAVs in complex traffic environments. However, current approaches still pose three major challenges: contextual adaptability, timely responsiveness, and effective multi-UAV coordination. In this paper, we introduce EnFlexiTwin, a digital twin enhancement assistance platform seamlessly integrated with AdaSor, a lightweight adaptive data selector. EnFlexiTwin automates the construction of incremental learning datasets, enabling real-time enhancements that allow digital twins to adapt to new time series data while preserving historical knowledge. We test EnFlexiTwin on a real-world dataset from low-altitude small-parcel delivery. The results show improved performance and adaptability of digital twins. Furthermore, time-varying simulations on real-world dataset and experiments on a practical air-ground cooperative UAV swarm application highlight that EnFlexiTwin achieves superior enhancements under varying real-time requirements and swarm scale compared to baseline approaches.", "keywords": [ "Adaptability", "Swarm behaviour", "Field (mathematics)", "Component (thermodynamics)", "Baseline (sea)", "Scale (ratio)", "Time series" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2025.3618724" }, { "id": "https://openalex.org/W7135210504", "doi": "10.5194/isprs-annals-x-3-w4-2025-349-2026", "title": "Human detection with YOLO for last-mile delivery applications using UAVs", "year": 2026, "publication_date": "2026-03-13", "type": "article", "language": "en", "authors": [ "Débora Paula Simões", "Henrique Cândido de Oliveira", "Rafael Lino dos Santos" ], "first_author": "Débora Paula Simões", "venue": "ISPRS annals of the photogrammetry, remote sensing and spatial information sciences", "publisher": "Copernicus Publications", "abstract": "Abstract. Low-cost alternative solutions have advanced last-mile delivery, with Unmanned Aerial Vehicles (UAVs) emerging as a promising option for logistics tasks. However, as UAV operations increasingly occur in densely crowded urban areas, safety concerns - especially for people nearby - have intensified. To ensure safe deliveries, real-time UAV path planning is essential for avoiding no-fly zones defined around individuals detected along the route. This study addresses this challenge by evaluating human detection confidence in UAV imagery using the YOLOv7 model and a custom dataset. It also estimates individuals’ positions through the Monoplotting technique. The customized YOLOv7 model achieved an average precision of 53.8% and an inference time of 9.9 ms, supporting real-time deployment. However, challenges in UAV-based human detection significantly influenced detection confidence. In one scenario, confidence exceeded 85% for individuals identified at a flight height of 30 m, while in another, the highest confidence reached 60% for imagery captured at 20 m. Despite numerous false negatives, the individual closest to the UAV was consistently detected, underscoring the applicability of the method for real-time path replanning. Regarding coordinate estimation of detected individuals, the Inertial Measurement Unit (IMU) system exerted the greatest influence on the accuracy of 3D positions obtained through Monoplotting. The phototriangulation process, which provided the sensor orientation parameters, directly impacted the results. To reduce discrepancies between estimated and actual coordinates, mathematical correction strategies may be applied; however, these require further investigation. The integration of Simultaneous Localization and Mapping (SLAM) techniques offers a promising direction for refining UAV rotation angles.", "keywords": [ "Inertial measurement unit", "Orientation (vector space)", "Photogrammetry", "Global Positioning System", "Path (computing)", "Inference", "Object detection", "Rotation (mathematics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://isprs-annals.copernicus.org/articles/X-3-W4-2025/349/2026/isprs-annals-X-3-W4-2025-349-2026.pdf" }, { "id": "https://openalex.org/W7140121014", "doi": "10.1016/j.procs.2026.02.393", "title": "Analysing the Operational Performance of Static and Dynamic Charging Solutions and the Sustainability Impact of Drone Enabled Last-Mile Delivery", "year": 2026, "publication_date": "2026-01-01", "type": "conference-paper", "language": "en", "authors": [ "Bek Nurzhanovich Tashkul", "Omid Fatahi Valilai" ], "first_author": "Bek Nurzhanovich Tashkul", "venue": "Procedia Computer Science", "publisher": "Elsevier BV", "abstract": "This research compares the operational performance of static and dynamic charging solutions for drone-enabled last-mile delivery. It also focuses on scalability and societal acceptance. To find efficient and sustainable solution, the combination of literature review, case analysis and survey research was applied. Among all models reviewed, Battery Swapping Systems (BSS), such as Droneport, stood out as the most quick and scalable approach. Due to its short turnaround time and low infrastructure demands it suits best high-density urban zones. To comprehend public opinion, a survey of 114 participants was conducted. The results showed that the end-customer are highly aware of the technology and sustainability factor emerged as a key motivator of support. Nevertheless, overall acceptance is closely related to the concerns about noise, safety and privacy. This paper also promotes scalable drone charging models and offers significant insights for policymakers and service providers about societal perception and readiness concerning urban logistics. The study incorporates a validated survey instrument and cross verifies findings using multiple case analyses and further studies considering the methodological limitations and the need for broader empirical validation in future research are suggested.", "keywords": [ "Drone", "Scalability", "Sustainability", "Key (lock)", "Empirical research", "Service (business)", "Open research", "Service provider" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.procs.2026.02.393" }, { "id": "https://openalex.org/W4403873129", "doi": "10.46354/i3m.2024.emss.014", "title": "Topology Effects in Drone Parcel Delivery", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Irene Izco", "Serrano Hernández, Adrián", "Faulín Fajardo, Javier" ], "first_author": "Irene Izco", "venue": null, "publisher": null, "abstract": "Despite the positive sustainability prospects of drones, their flight range is compromised due to their limited battery capacity and the payload of delivered parcels. An alternative to address this challenge is the placement of charging stations where drone batteries are recharged to expand their flying range. The aim of this work is determining the number and location of drone charging stations for topology-dependent scenarios: rural areas and densely populated urban areas. To the best of the researchers’ knowledge, there is currently no existing study in the literature that specifically investigates the impacts of topology on drone-assisted delivery. This study focuses on designing drone assignment strategies through optimization-simulation, aiming at minimizing charging station installation costs and operational costs and as a novelty, drone battery consumption is considered in the model design. Drone delivery order instances with different sizes and spatial distributions are generated to simulate realistic scenarios of demand and evaluate the optimization model to allocate the customer demands to stations and dimensioning drones fleet. Results show that considering parcel weight and flight distance has a significant impact on the performance of drone allocation to stations and highlight the effects of topology in the implementation of a drone-assisted delivery network.", "keywords": [ "Drone", "Computer science", "Topology (electrical circuits)", "Network topology", "Distributed computing", "Computer network", "Engineering", "Electrical engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.46354/i3m.2024.emss.014" }, { "id": "https://openalex.org/W7125900681", "doi": "10.6084/m9.figshare.31165219.v1", "title": "LCA harmonization for the last mile delivery sector", "year": 2026, "publication_date": "2026-01-01", "type": "other", "language": null, "authors": [ "Sinéad Mitchell" ], "first_author": "Sinéad Mitchell", "venue": "Figshare", "publisher": "Figshare (United Kingdom)", "abstract": "Several LCAs have been conducted to investigate the environmental impacts of drone delivery in the last-mile sector. The discussions predominantly revolve around the impacts of substituting fossil fuel alternatives for electrical options. However, it is currently not possible to conclude if one method generates less negative environmental impact than the other due to the great diversity of functional units used in each assessment.", "keywords": [ "Harmonization", "Environmental impact assessment", "Fossil fuel", "Diversity (politics)", "Government (linguistics)", "Ecological footprint", "Climate change" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.6084/m9.figshare.31165219.v1" }, { "id": "https://openalex.org/W4394777442", "doi": "10.22214/ijraset.2024.60039", "title": "SkyLogistics - The Complete Drone Delivery Solution", "year": 2024, "publication_date": "2024-04-12", "type": "article", "language": "en", "authors": [ "Chetan Rawarkar" ], "first_author": "Chetan Rawarkar", "venue": "International Journal for Research in Applied Science and Engineering Technology", "publisher": "International Journal for Research in Applied Science and Engineering Technology (IJRASET)", "abstract": "Abstract: SkyLogistics introduces an innovative drone delivery system aimed at transforming last-mile logistics. Fueled by the growing demand for swift and reliable package delivery solutions, our approach integrates hardware design, software development, and user interface enhancements to deliver seamless experiences. Extensive testing underscores SkyLogistics' exceptional delivery precision, speed, and customer satisfaction while complying with airspace regulations and safety standards. Overcoming challenges like regulatory conformity and scalability, SkyLogistics sets the stage for future advancements in dronebased transportation systems.", "keywords": [ "Drone", "Swift", "Scalability", "Computer science", "Interface (matter)", "Delivery system", "Systems engineering", "Last mile (transportation)", "Conformity assessment", "Software", "Embedded system", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.22214/ijraset.2024.60039" }, { "id": "https://openalex.org/W7125950175", "doi": "10.6084/m9.figshare.31165219", "title": "LCA harmonization for the last mile delivery sector", "year": 2026, "publication_date": "2026-01-28", "type": "conference-abstract", "language": null, "authors": [ "Sinéad Mitchell" ], "first_author": "Sinéad Mitchell", "venue": "Figshare", "publisher": "Figshare (United Kingdom)", "abstract": "Several LCAs have been conducted to investigate the environmental impacts of drone delivery in the last-mile sector. The discussions predominantly revolve around the impacts of substituting fossil fuel alternatives for electrical options. However, it is currently not possible to conclude if one method generates less negative environmental impact than the other due to the great diversity of functional units used in each assessment.", "keywords": [ "Harmonization", "Environmental impact assessment", "Fossil fuel", "Diversity (politics)", "Government (linguistics)", "Ecological footprint", "Climate change" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.6084/m9.figshare.31165219" }, { "id": "https://openalex.org/W3156544154", "doi": "10.1016/j.comnet.2021.108119", "title": "A novel resilient and reconfigurable swarm management scheme", "year": 2021, "publication_date": "2021-04-21", "type": "article", "language": "en", "authors": [ "Jamie Wubben", "Francisco Fabra", "Carlos T. Calafate", "Juan‐Carlos Cano", "Pietro Manzoni" ], "first_author": "Jamie Wubben", "venue": "Computer Networks", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Swarm behaviour", "Computer science", "Control reconfiguration", "Emulation", "Swarm robotics", "Robustness (evolution)", "Distributed computing", "Resilience (materials science)", "Real-time computing", "Embedded system", "Artificial intelligence" ], "cited_by_count": 23, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S138912862100195X" }, { "id": "https://openalex.org/W4412351362", "doi": "10.2139/ssrn.5348525", "title": "A Variable Neighborhood Search Algorithm for the Truck-Drone Routing Problem Under Uncertainty in Rural Last-Mile Delivery", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": "en", "authors": [ "Jianhua Xiao", "Hang Yu", "Jiuhong Xiao", "Yunyun Niu", "Xiaofan Wu" ], "first_author": "Jianhua Xiao", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Mile", "Truck", "Vehicle routing problem", "Variable (mathematics)", "Last mile (transportation)", "Routing (electronic design automation)", "Computer science", "Transport engineering", "Operations research", "Engineering", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5348525" }, { "id": "https://openalex.org/W7211954757", "doi": "10.1016/j.trip.2026.102241", "title": "Beyond the last mile: a systematic review of feasibility factors for drone deployment in logistics operations over the past decade", "year": 2026, "publication_date": "2026-09-08", "type": "review", "language": "en", "authors": [ "Bibek Yadav", "Jiaqing Lu", "Qianwen Guo", "Maxim A. Dulebenets" ], "first_author": "Bibek Yadav", "venue": "Transportation Research Interdisciplinary Perspectives", "publisher": "Elsevier BV", "abstract": "With the rapid development of e-commerce and increasing urbanization, an efficient management of logistics operations has become more challenging. Traditional logistics systems face limitations, such as road congestion, high operational costs, and sustainability concerns. Drone-based logistics, either as a drone only or drone integrated with traditional ground transportation, emerges as a promising solution, particularly for last-mile deliveries involving small and lightweight packages. Numerous studies have investigated hybrid logistics systems deploying drones within the existing transportation networks to enhance delivery speed, reduce operational costs, and support sustainable practices. The literature review conducted as part of this study critically and systematically evaluates the existing drone logistics research published over the past decade. The major objective is to assess the feasibility of integrating drones into logistics systems by examining technological, economic, and operational dimensions. The present survey study identifies and quantifies the key practical feasibility factors, including drone flight range limitations, payload restrictions, synchronization complexity, regulatory constraints, charging infrastructure availability, manufacturing capacities, and battery performance. Additionally, this review explores multi-agent interactions within different service sectors, analyzing how these interactions influence decision-making processes and the subsequent impact of drone integration from technical, economic, and operational perspectives. Moreover, a comprehensive framework for assessing the feasibility of drone and drone-assisted transportation services is presented as well. By analyzing a wide range of different factors, the present research explicitly showcases the potential of drone-based logistics solutions, their environmental impact, and the long-term implications for urban areas if drones are deployed for delivery by e-commerce companies.", "keywords": [ "Drone", "Software deployment", "Key (lock)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trip.2026.102241" }, { "id": "https://openalex.org/W4416904850", "doi": "10.3390/futuretransp5040181", "title": "A Heuristic Approach for Truck and Drone Delivery System", "year": 2025, "publication_date": "2025-12-01", "type": "article", "language": "en", "authors": [ "Sorin Ionut Conea", "Gloria Cerasela Crişan" ], "first_author": "Sorin Ionut Conea", "venue": "Future Transportation", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "In the rapidly evolving landscape of logistics and last-mile delivery, optimizing efficiency and minimizing costs are paramount. This paper introduces a novel heuristic approach designed to enhance the efficiency of a truck-and-drone delivery system. Our method addresses the complex challenge of coordinating the movements of a truck, which serves as a mobile depot, and an unmanned aerial vehicle (UAV or drone), which performs rapid, short-distance deliveries. Our system proposes a two-step heuristic. For truck routes, we utilized the Concorde Solver to determine the optimal path, based on real-world road distances between locations in Bacău County, Romania. This data was meticulously collected and processed as a Traveling Salesman Problem (TSP) instance with precise geographical information. Concurrently, a drone is deployed for specific deliveries, with routes calculated using the Haversine formula to determine accurate distances based on geographical coordinates. A crucial aspect of our model is the integration of the drone’s limited autonomy, ensuring that each mission adheres to its operational capacity. Computational experiments conducted on a real-world dataset including 93 localities from Bacău County, Romania, demonstrate the effectiveness of the proposed two-stage heuristic. Compared to the optimal truck-only route, the hybrid truck-and-drone system achieved up to 15.59% cost reduction and 38.69% delivery time savings, depending on the drone’s speed and autonomy parameters. These results confirm that the proposed approach can substantially enhance delivery efficiency in realistic distribution scenarios.", "keywords": [ "Drone", "Heuristic", "Solver", "Truck", "Travelling salesman problem", "Controller (irrigation)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2673-7590/5/4/181/pdf?version=1764555856" }, { "id": "https://openalex.org/W7126206360", "doi": "10.1109/jlt.2026.3659563", "title": "Development and Field Testing of a Robust UAV Relay-Assisted Hybrid FSO/RF System for Emergency Communications", "year": 2026, "publication_date": "2026-01-30", "type": "article", "language": null, "authors": [ "Weiyu Zhou", "Tingwei Wu", "Song Song", "Lun Zhao", "Daxue Wang", "Jie Li", "Li Zhou", "Hao Wen", "Yong Wang", "Lei Guo" ], "first_author": "Weiyu Zhou", "venue": "Journal of Lightwave Technology", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Conventional emergency communication networks are plagued by critical limitations, including protracted recovery cycles and coverage voids, which are further exacerbated by the escalating frequency of natural disasters and public safety incidents. To address these challenges, we propose an unmanned aerial vehicle relay-assisted hybrid free-space optical (FSO)/radio-frequency (RF) system engineered for rapid deployment and robust performance in emergency scenarios. In this architecture, FSO links form the high-capacity aerial backbone, while RF channels deliver last-mile connectivity to end users. Furthermore, a unified end-to-end channel model is developed to analytically integrate the effects of fiber attenuation, atmospheric turbulence, and RF path loss, establishing closed form relationships between received signal-to-noise ratio and bit error rate. Field experiments validate zero-bit-error transmission on the 100 m FSO relay link, a sustained downlink rate of 127.48 Mbps, and stable coverage, which collectively underscore the system's effectiveness for resilient, high-throughput emergency communications.", "keywords": [ "Software deployment", "Telecommunications link", "Channel (broadcasting)", "Path loss", "Transmission (telecommunications)", "Relay", "Bit error rate", "Wireless", "Emergency management" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/jlt.2026.3659563" }, { "id": "https://openalex.org/W4405513984", "doi": "10.2139/ssrn.5061024", "title": "Data Collection and Analytics Using Mobile Phones for Safe Landing and Takeoff Procedures of Last-Mile Delivery Drones", "year": 2024, "publication_date": "2024-01-01", "type": "preprint", "language": "en", "authors": [ "Joel Stenroos", "Harry Edelman", "Jussi Kalliola" ], "first_author": "Joel Stenroos", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Mile", "Drone", "Takeoff", "Aeronautics", "Analytics", "Last mile (transportation)", "Computer science", "Data collection", "Engineering", "Data science", "Aerospace engineering", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5061024" }, { "id": "https://openalex.org/W4386386963", "doi": "10.1038/s41598-023-41725-x", "title": "Author Correction: Critical assessment of emissions, costs, and time for last-mile goods delivery by drones versus truck", "year": 2023, "publication_date": "2023-09-02", "type": "erratum", "language": "en", "authors": [ "Aishwarya Raghunatha", "Emma Lindkvist", "Patrik Thollander", "Erika Hansson", "Greta Jonsson" ], "first_author": "Aishwarya Raghunatha", "venue": "Scientific Reports", "publisher": "Nature Portfolio", "abstract": "The original version of this Article contained an error in Figure 15, where the values for vertical and horizontal speed in the cruise phase and the vertical speed in the hover phase for landing were incorrect.", "keywords": [ "Truck", "Mile", "Drone", "Last mile (transportation)", "Aeronautics", "Computer science", "Transport engineering", "Environmental science", "Business", "Engineering", "Automotive engineering", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.nature.com/articles/s41598-023-41725-x.pdf" }, { "id": "https://openalex.org/W7204127130", "doi": "10.1109/jiot.2026.3726625", "title": "Enhancing Last-Mile Delivery: LLM-Evolved Clustering and DRL-Coordinated Routing in Truck–Multi-Drone Systems", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": null, "authors": [ "Hao Cheng", "Jin Yi", "Jun Luo", "Huayan Pu" ], "first_author": "Hao Cheng", "venue": "IEEE Internet of Things Journal", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": null, "keywords": [ "Cluster analysis", "Routing (electronic design automation)", "Algorithm design", "Routing protocol", "Network routing", "Intelligent Network" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/jiot.2026.3726625" }, { "id": "https://openalex.org/W4392236765", "doi": "10.1108/ir-01-2024-0022", "title": "The role of robots in logistics", "year": 2024, "publication_date": "2024-02-28", "type": "article", "language": "en", "authors": [ "Robert W. Bogue" ], "first_author": "Robert W. Bogue", "venue": "Industrial Robot the international journal of robotics research and application", "publisher": "Emerald Publishing Limited", "abstract": "Purpose The purpose of this paper is to illustrate the growing role of robots in the logistics industry. Design/methodology/approach Following an introduction, which identifies key challenges facing the industry, this paper discusses robotic applications in warehouses, followed by sections covering transportation and delivery and conclusions. Findings The logistics industry faces a number of challenges that drive technological and operational changes. Robots are already playing a role within the warehouse sector and more complex applications have recently arisen from developments in artificial intelligence-enabled vision technology. In the transportation sector, autonomous trucks are being developed and trialled by leading manufacturers. Many major logistics companies are involved and limited services are underway. Last-mile delivery applications are growing rapidly, and trials, pilot schemes and commercial services are underway in Europe, the USA and the Far East. The Chinese market is particularly buoyant, and in 2019, a delivery robot was launched that operates on public roads, based on Level-4 autonomous driving technology. The drone delivery sector has been slower to develop, in part due to regulatory constraints, but services are now being operated by drone manufacturers, retailers and logistics providers. Originality/value This paper provides details of existing and future applications of robots in the logistics industry.", "keywords": [ "Drone", "Robot", "Truck", "Business", "Originality", "Humanitarian Logistics", "Delivery Performance", "Engineering management", "Engineering", "Computer science", "Process management", "Artificial intelligence" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1108/ir-01-2024-0022" }, { "id": "https://openalex.org/W4401028087", "doi": "10.1007/978-3-031-60313-6_20", "title": "Critical Evaluation of Full Droneload (FDL) and Less-Than Droneload (LDL) in Drone-Based Last Mile Delivery", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Selwyn Piramuthu" ], "first_author": "Selwyn Piramuthu", "venue": "Progress in IS", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Computer science", "Geography", "Biology", "Geodesy" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-60313-6_20" }, { "id": "https://openalex.org/W7125964987", "doi": "10.12985/ksaa.2025.33.4.047", "title": "Safety Perceptions and Usage Intention in UAV-Based Last-Mile Logistics Services", "year": 2025, "publication_date": "2025-12-01", "type": "article", "language": "en", "authors": [ "Eun Bin Kim" ], "first_author": "Eun Bin Kim", "venue": "Journal of the Korean Society for Aviation and Aeronautics", "publisher": null, "abstract": "This study empirically analyzes the impact of safety factors on the intention to use Unmanned Aerial Vehicle (UAV)-based last-mile delivery services and examines the moderating effects of household characteristics. The results reveal that product safety significantly influences usage intention in a positive direction, while the moderating effect of single-person household status was partially confirmed. Specifically, the interaction effect between personal safety and single-person household status was significant, indicating that personal safety has a more important impact on UAV usage intention for single-person households. Although distance to parcel pickup point did not show a moderating effect on the relationship between safety perception and usage intention, it independently affected UAV usage intention, with the 100-500m distance group showing the highest intention. These findings suggest that UAV logistics service providers should prioritize product safety in service design and develop differentiated marketing strategies targeting single-person households while emphasizing personal safety features. The study contributes to the literature by identifying safety factors as key determinants of UAV service acceptance and highlighting the importance of considering users", "keywords": [ "Perception", "Risk perception", "Quality (philosophy)", "Context (archaeology)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.jksaa.org/download/download_pdf?pid=jksaa-33-4-47" }, { "id": "https://openalex.org/W7152079192", "doi": "10.3390/drones10040269", "title": "Multi-Station UAV–UGV Cooperative Delivery Scheduling Problem with Temporally Discontinuous Service Availability Under Diverse Urban Scenarios", "year": 2026, "publication_date": "2026-04-08", "type": "article", "language": "en", "authors": [ "Yinying Liu", "Jianmeng Liu", "X. Shi", "Cheng Tang" ], "first_author": "Yinying Liu", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Urban logistics systems face growing delivery demand and complex traffic and operational constraints, which make unmanned delivery carriers, including unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), a promising solution. Existing studies typically focus on a single delivery carrier type and rely on idealized assumptions, overlooking heterogeneous cooperation under multiple stations, multiple time windows, and real-world transport conditions. To address these gaps, we propose the Multi-Station UAV–UGV Cooperative Delivery Scheduling Problem with Temporally Discontinuous Service Availability (MSUUCDSP) to minimize the total travel and waiting time of UAVs and UGVs. To solve the problem, we propose a mixed-integer linear programming (MILP) model with a novel mathematical approach and a Hybrid Large Neighborhood Search (HLNS) algorithm. Additionally, we adopt a Hidden Markov Model (HMM)-based map-matching method and big data techniques to capture realistic operational characteristics. Computational experiments are conducted on various realistic instances under four diverse scenarios. Results show that UAV–UGV cooperation significantly improves efficiency, reducing total time cost by 17.12% compared with single-mode delivery, and they reveal substantial discrepancies between idealized assumptions and realistic scenarios. We further develop an ArcGIS-based simulation to support practical implementation. The findings provide valuable insights for decision-making and engineering applications for logistics operators.", "keywords": [ "Scheduling (production processes)", "Markov decision process", "Markov chain", "Job shop scheduling", "Drone", "Service (business)", "Linear programming" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/10/4/269/pdf?version=1775652556" }, { "id": "https://openalex.org/W4401281286", "doi": "10.1007/978-981-97-5098-6_104", "title": "Urban Logistics Drone Delivery Route Planning: An Application of Operation Research Towards Smart Cities", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Rui Qiu", "Yu Ding", "Jidi Cao", "Shuhua Hou" ], "first_author": "Rui Qiu", "venue": "Lecture notes on data engineering and communications technologies", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Drone", "City logistics", "Transport engineering", "Business", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-981-97-5098-6_104" }, { "id": "https://openalex.org/W4321020402", "doi": "10.1109/sii55687.2023.10039137", "title": "Drone airfield location determination method for parcel delivery by vehicle and drone", "year": 2023, "publication_date": "2023-01-17", "type": "conference-paper", "language": "en", "authors": [ "Satoru Hori", "Norihisa Komoda", "Takenao Ohkawa" ], "first_author": "Satoru Hori", "venue": "2023 IEEE/SICE International Symposium on System Integration (SII)", "publisher": null, "abstract": "While the e-commerce market has been expanding in recent years, some regions are facing a shortage of delivery drivers due to the declining birthrate and aging population, and so securing a delivery network is beginning to become a societal issue. For this reason, there are growing expectations for the use of drones to improve the efficiency of delivery. In this study, a method for determining drone airfields to realize efficient delivery through the coordination of a vehicle and a drone is proposed. In this method, road locations close to the average of the locations of residences belonging to each cluster calculated using the K-means method is selected as candidate locations for a drone airfield. Among the candidates, the location that minimizes the sum of travel time to the residences belonging to the cluster is selected as the location of the drone airfields. Through simulation evaluation, it was confirmed that the number of packages that can be delivered within the specified time slot increases, and the time required for delivery is reduced compared to the case where the location on the road closest to the average of the locations of residences belonging to each cluster calculated using the K-means method is used as the location of the drone airfields.", "keywords": [ "Drone", "Cluster (spacecraft)", "Economic shortage", "Computer science", "Travel time", "Population", "Transport engineering", "Operations research", "Engineering", "Computer network", "Demography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://da.lib.kobe-u.ac.jp/da/kernel/0100485253/0100485253.pdf" }, { "id": "https://openalex.org/W4404304659", "doi": "10.48550/arxiv.2410.17392", "title": "Experimental Designs for Optimizing Last-Mile Delivery", "year": 2024, "publication_date": "2024-10-22", "type": "preprint", "language": "en", "authors": [ "Nicholas Rios", "Jie Xu" ], "first_author": "Nicholas Rios", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "Companies like Amazon and UPS are heavily invested in last-mile delivery problems. Optimizing last-delivery operations not only creates tremendous cost savings for these companies but also generate broader societal and environmental benefits in terms of better delivery service and reduced air pollutants and greenhouse gas emissions. Last-mile delivery is readily formulated as the Travelling Salesman Problem (TSP), where a salesperson must visit several cities and return to the origin with the least cost. A solution to this problem is a Hamiltonian circuit in an undirected graph. Many methods exist for solving the TSP, but they often assume the travel costs are fixed. In practice, travel costs between delivery zones are random quantities, as they are subject to variation from traffic, weather, and other factors. Innovations such as truck-drone last-mile delivery creates even more uncertainties due to scarce data. A Bayesian D-optimal experimental design in conjunction with a regression model are proposed to estimate these unknown travel costs, and subsequently search for a highly efficient solution to the TSP. This framework can naturally be extended to incorporate the use of drones and any other emerging technology that has use in last-mile delivery.", "keywords": [ "Mile", "Last mile (transportation)", "Computer science", "Geography", "Geodesy" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2410.17392" }, { "id": "https://openalex.org/W7204097285", "doi": "10.17632/rv2c7768hp", "title": "Replication package: Flight Authorization and Emissions Abatement in Truck-Drone Last-Mile Delivery: An Optimization-Based Counterfactual Analysis", "year": 2026, "publication_date": "2026-09-17", "type": "dataset", "language": null, "authors": [ "Armin Mahmoodi", "Mehdi Davoodi", "Seyed Mojtaba Sajadi", "Elnaz Torkamani", "Said M. Easa" ], "first_author": "Armin Mahmoodi", "venue": "Mendeley Data", "publisher": null, "abstract": "Code and results supporting the article \"Flight Authorization and Emissions Abatement in Truck-Drone Last-Mile Delivery: An Optimization-Based Counterfactual Analysis\", on how airspace flight authorization limits the emissions abatement achievable by hybrid truck-drone last-mile delivery. The code implements a multi-objective truck-UAV routing model in which emissions are an output of the routing decision rather than an assumption about it: a momentum-theory energy model with payload dependence in place of a distance proxy, well-to-wheel emissions accounting, an explicit truck-only counterfactual solved on the same instances, and SORA-derived authorization limits entering as arc eligibility. Twelve operating scenarios vary the authorization ceiling, population density and whether a sheltering mitigation is claimed, repeated across five independently generated service areas. Solutions come from NSGA-II and MOPSO over a shared random-key encoding, validated against proven optima from a mixed-integer program on small instances; a no-aerial control scenario measures the resolution of the comparison. CONTENTS. code/ holds the model package (tdrp/) and the scripts that produce every reported result: run_multigeo.py for the main experiment, run_evan.py for the electric-van counterfactual, seed_scaling.py for the measurement-resolution diagnostic, run_validation.py and test_validation.py for validation against exact optima, run_algorithms.py for the algorithm comparison, run_tuning.py with the tuned parameter files, and make_figs_multigeo.py, make_figs_converged.py and make_fronts.py for the figures. results/ holds the result files behind every table and figure, including same-code Linux re-runs cited as such in the article. logs/ holds the output logs against which each reported value can be checked; two of them regenerate byte-for-byte from the result files. figures/ holds the figure files, sources/ the submitted manuscript, title page, supplementary material and bibliography. ASSUMPTIONS_REGISTER.md documents each modelling choice and its provenance; DEPOSIT_CONTENTS.md is the file inventory. The reported emissions results are in results/results_multigeo_50seed.json: five service areas, twelve scenarios each, 2000 generations, 50 seeds, with the truck-only counterfactual solved once per seed and selected on minimum cost. Reproduction requires Python 3.10 or newer with NumPy pinned to 2.4.4 (code/requirements.txt); NumPy gives no guarantee that its random streams are stable across versions, so a different version changes every seeded run. code/HOW_TO_RUN.md gives the commands, the expected output at each stage and the values to check against. Instances are determined entirely by customer count, scenario and random seed, so any result regenerates exactly on a matching environment. Version 2 replaces the sources with the submitted versions and adds requirements.txt, HOW_TO_RUN.md, the Linux re-run files and the regenerated figures.", "keywords": [ "Counterfactual thinking", "Population", "Payload (computing)", "Python (programming language)", "Scripting language", "Replication (statistics)", "Greenhouse gas" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.17632/rv2c7768hp" }, { "id": "https://openalex.org/W7106098929", "doi": "10.4018/979-8-3373-2843-0.ch004", "title": "AI and Autonomous Vehicles in Last-Mile Delivery", "year": 2025, "publication_date": "2025-11-20", "type": "book-chapter", "language": null, "authors": [ "S. Ida Evangeline" ], "first_author": "S. Ida Evangeline", "venue": "Advances in computational intelligence and robotics book series", "publisher": "IGI Global", "abstract": "This chapter explores the transformative impact of Artificial Intelligence (AI) and autonomous vehicle technologies on last-mile delivery, a critical yet complex segment of modern supply chains. With the increase of e-commerce and on demand services, the traditional last mile logistics is facing more and more challenges such as traffic congestion, inefficient routing, high operational cost and limited visibility. In response, AI driven solutions, like predictive analytics, dynamic route optimization, and autonomous fleet coordination, are empowering smarter, more transparent and efficient delivery systems. Self driving vans, drones and sidewalk robots are increasingly being deployed to reduce delivery times, cut emissions and improve real time monitoring. The chapter also discusses how AI integrated technologies such as IoT sensors, blockchain and computer vision improve supply chain transparency, authentication and security.", "keywords": [ "Drone", "Supply chain", "Robot", "Transformative learning", "Internet of Things", "Cloud computing", "Robotics", "Emerging technologies" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.4018/979-8-3373-2843-0.ch004" }, { "id": "https://openalex.org/W7213512513", "doi": "10.17632/rv2c7768hp.3", "title": "Replication package: Flight Authorization and Emissions Abatement in Truck-Drone Last-Mile Delivery: An Optimization-Based Counterfactual Analysis", "year": 2026, "publication_date": "2026-09-17", "type": "dataset", "language": null, "authors": [ "Armin Mahmoodi", "Mehdi Davoodi", "Seyed Mojtaba Sajadi", "Elnaz Torkamani", "Said Easa" ], "first_author": "Armin Mahmoodi", "venue": "Mendeley Data", "publisher": null, "abstract": "Code and results supporting the article \"Flight Authorization and Emissions Abatement in Truck-Drone Last-Mile Delivery: An Optimization-Based Counterfactual Analysis\", on how airspace flight authorization limits the emissions abatement achievable by hybrid truck-drone last-mile delivery. The code implements a multi-objective truck-UAV routing model in which emissions are an output of the routing decision rather than an assumption about it: a momentum-theory energy model with payload dependence in place of a distance proxy, well-to-wheel emissions accounting, an explicit truck-only counterfactual solved on the same instances, and SORA-derived authorization limits entering as arc eligibility. Twelve operating scenarios vary the authorization ceiling, population density and whether a sheltering mitigation is claimed, repeated across five independently generated service areas. Solutions come from NSGA-II and MOPSO over a shared random-key encoding, validated against proven optima from a mixed-integer program on small instances; a no-aerial control scenario measures the resolution of the comparison. CONTENTS. code/ holds the model package (tdrp/) and the scripts that produce every reported result: run_multigeo.py for the main experiment, run_evan.py for the electric-van counterfactual, seed_scaling.py for the measurement-resolution diagnostic, run_validation.py and test_validation.py for validation against exact optima, run_algorithms.py for the algorithm comparison, run_tuning.py with the tuned parameter files, and make_figs_multigeo.py, make_figs_converged.py and make_fronts.py for the figures. results/ holds the result files behind every table and figure, including same-code Linux re-runs cited as such in the article. logs/ holds the output logs against which each reported value can be checked; two of them regenerate byte-for-byte from the result files. figures/ holds the figure files, sources/ the submitted manuscript, title page, supplementary material and bibliography. ASSUMPTIONS_REGISTER.md documents each modelling choice and its provenance; DEPOSIT_CONTENTS.md is the file inventory. The reported emissions results are in results/results_multigeo_50seed.json: five service areas, twelve scenarios each, 2000 generations, 50 seeds, with the truck-only counterfactual solved once per seed and selected on minimum cost. Reproduction requires Python 3.10 or newer with NumPy pinned to 2.4.4 (code/requirements.txt); NumPy gives no guarantee that its random streams are stable across versions, so a different version changes every seeded run. code/HOW_TO_RUN.md gives the commands, the expected output at each stage and the values to check against. Instances are determined entirely by customer count, scenario and random seed, so any result regenerates exactly on a matching environment. Version 2 replaces the sources with the submitted versions and adds requirements.txt, HOW_TO_RUN.md, the Linux re-run files and the regenerated figures.", "keywords": [ "Counterfactual thinking", "Payload (computing)", "Population", "Replication (statistics)", "Code (set theory)", "Control (management)", "Authorization", "Service (business)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.17632/rv2c7768hp.3" }, { "id": "https://openalex.org/W3211119726", "doi": "10.1007/978-3-030-83144-8_3", "title": "Use-Cases for Heavy Lift Unmanned Cargo Aircraft", "year": 2021, "publication_date": "2021-11-02", "type": "book-chapter", "language": "en", "authors": [ "Henry Pak" ], "first_author": "Henry Pak", "venue": "Research topics in aerospace", "publisher": "Springer Nature", "abstract": null, "keywords": [ "Drone", "Spare part", "Payload (computing)", "Last mile (transportation)", "Lift (data mining)", "Airplane", "Aeronautics", "Computer science", "Engineering", "Transport engineering", "Marine engineering", "Aerospace engineering" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-030-83144-8_3" }, { "id": "https://openalex.org/W7213415692", "doi": "10.17632/rv2c7768hp.2", "title": "Replication package: Flight Authorization and Emissions Abatement in Truck-Drone Last-Mile Delivery: An Optimization-Based Counterfactual Analysis", "year": 2026, "publication_date": "2026-09-16", "type": "dataset", "language": null, "authors": [ "Armin Mahmoodi", "Mehdi Davoodi", "Seyed Mojtaba Sajadi", "Elnaz Torkamani", "Said Easa" ], "first_author": "Armin Mahmoodi", "venue": "Mendeley Data", "publisher": null, "abstract": "Code and results supporting the article \"Flight Authorization and Emissions Abatement in Truck-Drone Last-Mile Delivery: An Optimization-Based Counterfactual Analysis\", on how airspace flight authorization limits the emissions abatement achievable by hybrid truck-drone last-mile delivery. The code implements a multi-objective truck-UAV routing model in which emissions are an output of the routing decision rather than an assumption about it: a momentum-theory energy model with payload dependence in place of a distance proxy, well-to-wheel emissions accounting, an explicit truck-only counterfactual solved on the same instances, and SORA-derived authorization limits entering as arc eligibility. Twelve operating scenarios vary the authorization ceiling, population density and whether a sheltering mitigation is claimed, repeated across five independently generated service areas. Solutions come from NSGA-II and MOPSO over a shared random-key encoding, validated against proven optima from a mixed-integer program on small instances; a no-aerial control scenario measures the resolution of the comparison. CONTENTS. code/ holds the model package (tdrp/) and the scripts that produce every reported result: run_multigeo.py for the main experiment, run_evan.py for the electric-van counterfactual, seed_scaling.py for the measurement-resolution diagnostic, run_validation.py and test_validation.py for validation against exact optima, run_algorithms.py for the algorithm comparison, run_tuning.py with the tuned parameter files, and make_figs_multigeo.py, make_figs_converged.py and make_fronts.py for the figures. results/ holds the result files behind every table and figure, including same-code Linux re-runs cited as such in the article. logs/ holds the output logs against which each reported value can be checked; two of them regenerate byte-for-byte from the result files. figures/ holds the figure files, sources/ the submitted manuscript, title page, supplementary material and bibliography. ASSUMPTIONS_REGISTER.md documents each modelling choice and its provenance; DEPOSIT_CONTENTS.md is the file inventory. The reported emissions results are in results/results_multigeo_50seed.json: five service areas, twelve scenarios each, 2000 generations, 50 seeds, with the truck-only counterfactual solved once per seed and selected on minimum cost. Reproduction requires Python 3.10 or newer with NumPy pinned to 2.4.4 (code/requirements.txt); NumPy gives no guarantee that its random streams are stable across versions, so a different version changes every seeded run. code/HOW_TO_RUN.md gives the commands, the expected output at each stage and the values to check against. Instances are determined entirely by customer count, scenario and random seed, so any result regenerates exactly on a matching environment. Version 2 replaces the sources with the submitted versions and adds requirements.txt, HOW_TO_RUN.md, the Linux re-run files and the regenerated figures.", "keywords": [ "Counterfactual thinking", "Payload (computing)", "Population", "Replication (statistics)", "Code (set theory)", "Control (management)", "Authorization", "Service (business)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.17632/rv2c7768hp.2" }, { "id": "https://openalex.org/W4399145584", "doi": "10.2139/ssrn.4846772", "title": "The Truck-Drone Routing Problem Under Uncertainty in Rural Last-Mile Delivery: An Improved Variable Neighborhood Search Metaheuristic", "year": 2024, "publication_date": "2024-01-01", "type": "preprint", "language": "en", "authors": [ "Jianhua Xiao", "Jiuhong Xiao", "Ying Li", "Yunyun Niu", "Xiaofan Wu" ], "first_author": "Jianhua Xiao", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Mile", "Metaheuristic", "Variable neighborhood search", "Last mile (transportation)", "Vehicle routing problem", "Routing (electronic design automation)", "Variable (mathematics)", "Computer science", "Transport engineering", "Operations research" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4846772" }, { "id": "https://openalex.org/W7206214458", "doi": "10.1109/dtisd69661.2026.11668305", "title": "Prospects for Drone-Based Last-Mile Delivery in Major Urban Centres: Empirical Evidence from Can Tho City", "year": 2026, "publication_date": "2026-07-01", "type": "conference-paper", "language": null, "authors": [ "Tuan-Kiet H.V. Truong", "Uyen Thi Thao Tieu" ], "first_author": "Tuan-Kiet H.V. Truong", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Empirical evidence", "Empirical research", "Government (linguistics)", "Scope (computer science)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/dtisd69661.2026.11668305" }, { "id": "https://openalex.org/W7214396631", "doi": "10.5281/zenodo.22949613", "title": "Data and code for \"When are delivery drones worth retaining? Multimodal last-mile planning across terrain and access conditions\"", "year": 2026, "publication_date": "2026-09-25", "type": "dataset", "language": "en", "authors": [ "Liang-Cheng Chang" ], "first_author": "Liang-Cheng Chang", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "This record contains the research inputs, model code, saved route-search outputs, customer-level access screens, hub-layout and access-envelope sensitivities, small-instance exact-check outputs, and separately labelled route-level stress diagnostics supporting the manuscript “When are delivery drones worth retaining? Multimodal last-mile planning across terrain and access conditions.” The study uses four contrasting road-network cases and twelve spatially resampled sets of 120 synthetic customers. Customer locations are sampled from mapped network nodes; they are not observed customer addresses or carrier orders. Operating costs, service rules, energy rates, and emissions are model scenarios, not field-measured delivery outcomes. The large-instance heuristic reports best-found plans, not certified global optima. The release is frozen to the evidence lineage used by the manuscript. Later demand-release and route experiments in the working research archive are not included as evidence for the manuscript. The archive includes OpenStreetMap-derived road-network inputs, Taiwan Ministry of the Interior 20 m DTM-derived processed road-edge fields, Amazon-derived planned service-duration values, original code, synthetic instances, and generated results. It does not redistribute raw DTM rasters or the original Amazon dataset. See README.md and LICENSES_AND_ATTRIBUTION.md inside the archive for provenance, reuse conditions, and reproduction notes.", "keywords": [ "Drone", "Terrain", "Certification", "Reuse", "Code (set theory)", "Heuristic", "Service (business)", "Christian ministry", "Geospatial analysis" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.22949613" }, { "id": "https://openalex.org/W7117733549", "doi": "10.1109/wincom65874.2025.11313401", "title": "ML-Based UAV Routing with Dynamic Geofencing Using 5G NEF and CAMARA APIs", "year": 2025, "publication_date": "2025-11-25", "type": "conference-paper", "language": "en", "authors": [ "Wassim Kribaa", "Miloud Bagaa", "Ibrahim Afolabi", "Adlen Ksentini", "Mohammed Salem Elmusrati", "Petri O. Välisuo" ], "first_author": "Wassim Kribaa", "venue": null, "publisher": null, "abstract": "In dense urban environments, traditional GNSS-based navigation for Unmanned Aerial Vehicles (UAVs) suffers from multipath interference and signal obstructions, compromising positioning accuracy and increasing risks of collisions and airspace violations. This paper proposes a novel machine learning-based system architecture for autonomous UAV parcel delivery, leveraging standardized 5G Network Exposure Function (NEF) and CAMARA Device Location API to achieve sub-meter location precision. Our approach integrates dynamic geofencing and predictive rerouting at the network edge, powered by a Random Forest-based collision prediction model that proactively adjusts UAV trajectories to avoid restricted zones in real time. Through simulations of six UAVs navigating dynamically updated no-fly zones, we demonstrate that our system significantly reduces time spent in restricted areas to near zero, compared to GNSS-only and rule-based methods, while limiting path-length inflation to approximately 30% for five of six flights. These results underscore the potential of combining 5G-enabled location services with edge intelligence to enhance safety and compliance in urban UAV operations.", "keywords": [ "Multipath propagation", "Limiting", "Drone", "Routing (electronic design automation)", "Interference (communication)", "Enhanced Data Rates for GSM Evolution", "Function (biology)", "Base station", "Trajectory" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/wincom65874.2025.11313401" }, { "id": "https://openalex.org/W4415399745", "doi": "10.1109/aimv66517.2025.11203569", "title": "Optimizing Parcel Delivery: The Role of Drones in Modern Logistics", "year": 2025, "publication_date": "2025-08-16", "type": "conference-paper", "language": null, "authors": [ "Keni Tandel", "Niya Patel", "Samir Patel" ], "first_author": "Keni Tandel", "venue": null, "publisher": null, "abstract": "Online shopping has been more popular in recent years, which has resulted in a rise in parcel deliveries. In the past, parcel distribution by truck was an efficient method. However, with developing technologies, deliveries can now be conducted using unmanned air vehicles such as drones. This study paper explains the use of drones in logistics and compares them to traditional delivery techniques in order to develop optimized delivery methods. Deliveries with drones require various critical components, such as determining the trajectory or path to be taken, weight limitations, battery life, and drone speed. Using these drone features and designing a path that includes the warehouse, charging station, and as many delivery destinations as feasible transforms the logistics industry into a smart transport firm. This can be accomplished using a variety of techniques, including the traveling salesman problem, routing problem, and combinatorial optimization. Additionally, deploying multiple drones for distribution is advantageous. This research study examines how parcel delivery might be enhanced to improve the logistics industry. To employ drones, companies must grasp networking and computer vision technology. Drone delivery relies on computer vision to perceive and analyze surrounding data in real time. In the final stage of delivery (last mile delivery), computer vision is used to authenticate or verify the delivery address. All of these aspects and components come together to make smart transportation a reality.", "keywords": [ "Drone", "Variety (cybernetics)", "Last mile (transportation)", "Travelling salesman problem", "Destinations", "Path (computing)", "Truck", "Delivery Performance" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/aimv66517.2025.11203569" }, { "id": "https://openalex.org/W7214289476", "doi": "10.5281/zenodo.22949614", "title": "Data and code for \"When are delivery drones worth retaining? Multimodal last-mile planning across terrain and access conditions\"", "year": 2026, "publication_date": "2026-09-25", "type": "dataset", "language": "en", "authors": [ "Liang-Cheng Chang" ], "first_author": "Liang-Cheng Chang", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "This record contains the research inputs, model code, saved route-search outputs, customer-level access screens, hub-layout and access-envelope sensitivities, small-instance exact-check outputs, and separately labelled route-level stress diagnostics supporting the manuscript “When are delivery drones worth retaining? Multimodal last-mile planning across terrain and access conditions.” The study uses four contrasting road-network cases and twelve spatially resampled sets of 120 synthetic customers. Customer locations are sampled from mapped network nodes; they are not observed customer addresses or carrier orders. Operating costs, service rules, energy rates, and emissions are model scenarios, not field-measured delivery outcomes. The large-instance heuristic reports best-found plans, not certified global optima. The release is frozen to the evidence lineage used by the manuscript. Later demand-release and route experiments in the working research archive are not included as evidence for the manuscript. The archive includes OpenStreetMap-derived road-network inputs, Taiwan Ministry of the Interior 20 m DTM-derived processed road-edge fields, Amazon-derived planned service-duration values, original code, synthetic instances, and generated results. It does not redistribute raw DTM rasters or the original Amazon dataset. See README.md and LICENSES_AND_ATTRIBUTION.md inside the archive for provenance, reuse conditions, and reproduction notes.", "keywords": [ "Drone", "Terrain", "Certification", "Reuse", "Code (set theory)", "Heuristic", "Service (business)", "Christian ministry", "Geospatial analysis" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.22949614" }, { "id": "https://openalex.org/W7117584921", "doi": "10.37634/efp.2025.12.7", "title": "Assessment of economic and environmental efficiency of unmanned aerial vehicles in green city logistics", "year": 2025, "publication_date": "2025-12-01", "type": "article", "language": null, "authors": [ "Oleksandr TSAPENKO", "Наталія Семченко", "Kateryna Razumova", "Oksana Kyrylenko" ], "first_author": "Oleksandr TSAPENKO", "venue": "Economics Finances Law", "publisher": null, "abstract": "The paper aims to confirm the high demand for Unmanned Aerial Vehicles in urban logistics, highlighting the essence and composition of and the potential to reduce delivery costs and improve urban sustainability, emphasizing the growing importance of last-mile logistics. The practical significance of the research results lies in assessing external and internal costs, which provides a comprehensive and responsible approach to planning and organizing urban transportation of small loads, which are the object of last-mile logistics. The basic parameters of both transport options were determined, including technical characteristics, route structure and duration, and direct internal costs (wages, depreciation, fuel/electricity, repair and maintenance, other operating costs) and external costs (road accidents, air pollution, climate change impact, noise, congestion) are calculated. The calculation model is based on a two-dimensional approach to cost analysis, which makes it possible the assessment of the economic, social and environmental impact of delivery. The calculation result shows the advantages of using systems of unmanned aerial vehicles for delivery compared to cars. It shows that introducing a drone into operation can be an affordable delivery method, especially considering internal and external costs. The calculation algorithm is a valuable tool for planning and improving the \"last mile\" delivery processes, particularly for solving the difficulties of optimizing costs, reducing environmental impact, and ensuring sustainable development and quality of services, considering various aspects affecting the economy, society, and the environment. The work results are proposed to be considered when planning policies and incentives to support new challenges in urban delivery, as well as for the formation of policies and incentives aimed at the implementation of environmentally friendly transportation technologies.", "keywords": [ "Incentive", "Drone", "Work (physics)", "Sustainable development", "Urban planning", "Environmental impact assessment", "Air quality index", "Quality (philosophy)", "Sustainable transport" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.37634/efp.2025.12.7" }, { "id": "https://openalex.org/W7160901561", "doi": "10.46254/gc03.20250304", "title": "Drone Delivery in Saudi Arabia: Public Awareness and Challenges", "year": 2026, "publication_date": "2026-02-02", "type": "conference-paper", "language": null, "authors": [ "Saja Bahabri", "Nawal Salamah", "Linah Alnumani", "Mawadah Al Yazidi" ], "first_author": "Saja Bahabri", "venue": null, "publisher": null, "abstract": "Last-mile delivery represents the most challenging and expensive stage in logistics, accounting for nearly half of total transportation costs. As e-commerce expands in Saudi Arabia, companies seek innovative methods to improve delivery speed and sustainability. Drone delivery has emerged as a promising solution to overcome urban congestion, high costs, and environmental impacts. This research investigates public perception, awareness, and willingness to adopt drone delivery in Saudi Arabia through a quantitative survey distributed to a diverse sample of participants. The survey explores factors such as safety, reliability, cost, convenience, and environmental benefits influencing consumer acceptance. The findings are expected to identify key opportunities and challenges for implementing drone delivery systems, offering insights for logistics firms and policymakers aiming to enhance last-mile efficiency. The study also aligns with Vision 2030’s goals of digital transformation and sustainable urban logistics.", "keywords": [ "Drone", "Government (linguistics)", "Pandemic", "Action (physics)", "Context (archaeology)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieomsociety.org/proceedings/saudiarabia2025/304.pdf" }, { "id": "https://openalex.org/W7127791533", "doi": null, "title": "Economics of transport and logistics. Last mile logistics", "year": 2023, "publication_date": "2023-07-08", "type": "dissertation", "language": "es", "authors": [ "Adrián Pisano García" ], "first_author": "Adrián Pisano García", "venue": "UCrea (University of Cantabria)", "publisher": "Universidad de Cantabria", "abstract": "La evolución de la sociedad, la densidad de la población y los avances tecnológicos han conseguido que en los últimos años el comercio online se haya convertido en la mayor forma de compra de la gran mayoría de la población. Esto hizo variar los hábitos de consumo de familias pasando de acudir frecuentemente a tiendas físicas a fomentar la tienda online, las entregas a domicilio o puntos de entrega de paquetes. Como consecuencia de esta nueva forma de consumir hizo que las entregas a domicilio se dispararan exponencialmente. La logística ha marcado un antes y un después en el mundo empresarial. A través del paso del tiempo y sobre todo posteriormente a la época COVID-19 las empresas comenzaron a recibir diversas peticiones a la hora de entregar los paquetes. Todo este proceso tuvo sus ventajas y desventajas, siendo la distribución de la última milla la mayor preocupación para las empresas. Surgieron numerosos problemas, para los cuales ya se había encontrado una solución. Con este trabajo de fin de grado busco analizar las soluciones ya halladas e investigar sobre los nuevos TICS asociados a la última milla. Se realizará un análisis del proceso reparto de paquetería con drones, donde se expondrá una encuesta a diferentes públicos, con la cual se buscará extraer un análisis de datos con la finalidad de obtener la información suficiente sobre ello para realizar una implantación de ello en una ciudad como Santander.", "keywords": [ "Economic shortage", "Revenue" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/10902/32403" }, { "id": "https://openalex.org/W7202343479", "doi": "10.1016/j.jclepro.2026.149168", "title": "Instrumental and normative rationality as dual drivers of sustainable consumption intentions: A study of usage and payment intentions for drone last-mile delivery", "year": 2026, "publication_date": "2026-08-13", "type": "article", "language": "en", "authors": [ "Junjie Dong", "Jian-chao Liu", "Xuan-yi Pan", "Yuankai Huang" ], "first_author": "Junjie Dong", "venue": "Journal of Cleaner Production", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Normative", "Rationality", "Dual (grammatical number)", "Payment", "Consumption (sociology)", "Sustainable consumption" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.jclepro.2026.149168" }, { "id": "https://openalex.org/W4281696834", "doi": "10.1121/10.0011546", "title": "Auditory detection probability of propeller noise in hover flight in presence of ambient soundscape", "year": 2022, "publication_date": "2022-06-01", "type": "article", "language": "en", "authors": [ "Oksana Stalnov", "Michael Faran", "Yonatan Koral", "Miriam Furst" ], "first_author": "Oksana Stalnov", "venue": "The Journal of the Acoustical Society of America", "publisher": "Acoustical Society of America", "abstract": "Unmanned aerial vehicles are rapidly advancing and becoming ubiquitous in an unlimited number of applications, from parcel delivery to people transportation. As unmanned aerial vehicle (UAV) markets expand, the increased acoustic nuisance on population becomes a more acute problem. Previous aircraft noise assessments have highlighted the necessity of a psychoacoustic metric for quantification of human audio perception. This study presents a framework for estimating propeller-based UAV auditory detection probability on the ground for a listener in a real-life scenario. The detection probability is derived by using its free-field measured acoustic background and estimating the UAV threshold according to a physiological model of the auditory pathway. The method is presented via results of an exemplar measurement in an anechoic environment with a single two- and five-bladed propeller. It was found that the auditory detection probability is primarily affected by the background noise level, whereas the number of blades is a less significant parameter. The significance of the proposed method lies in providing a quantitative evaluation of auditory detection probability of the UAV on the ground in the presence of a given soundscape. The results of this work are of practical significance since the method can aid anyone who plans a hovering flight mode.", "keywords": [ "Acoustics", "Computer science", "Noise (video)", "Soundscape", "Anechoic chamber", "Propeller", "Psychoacoustics", "Ambient noise level", "Metric (unit)", "Population", "Background noise", "Perception" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1121/10.0011546" }, { "id": "https://openalex.org/W7171154675", "doi": "10.17605/osf.io/sfj47", "title": "Last Mile Delivery Optimization Integrating Autonomous UAVs: A Systematic Literature Review", "year": 2026, "publication_date": "2026-07-22", "type": "preprint", "language": null, "authors": [ "Iyed Nasra" ], "first_author": "Iyed Nasra", "venue": null, "publisher": null, "abstract": "This systematic literature review synthesizes research on optimization models, problem formulations, and solution methods applied to autonomous UAV-assisted last-mile delivery problems (e.g., FSTSP, PDSVRP, VRPD, TDDP). It classifies problem variants, operational constraint formulations (time windows, capacity, battery limits, payload weight, weather, no-fly zones), and solution methodologies across exact mathematical programming (MILP, MINLP, Branch-and-X, Benders), heuristics/metaheuristics (single-solution, population-based, hybrid, matheuristics, multi-objective), and emerging ML/DRL-hybridized optimization.", "keywords": [ "Systematic review", "Payload (computing)", "Constraint (computer-aided design)", "Component (thermodynamics)", "Optimization problem", "Work (physics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://osf.io/sfj47" }, { "id": "https://openalex.org/W7128235602", "doi": "10.5821/dissertation-2117-454074", "title": "Optimizing two-echelon city logistics with autonomous vehicles: an integrated assessment framework for sustainable last-mile deliveries", "year": 2024, "publication_date": "2024-11-04", "type": "dissertation", "language": "en", "authors": [ "Clément Lemardelé" ], "first_author": "Clément Lemardelé", "venue": null, "publisher": null, "abstract": "(English) As the improvement of last-mile logistics operations becomes a more and more pressing challenge to make our cities more sustainable, both from an economic and environmental perspective, a wide sample of new technologies and innovative distribution schemes are currently being piloted by logistics companies and studied within the research community. Beyond the necessary shift in the powertrain technologies, from internal combustion engine vehicles to electric ones, more efficient delivery strategies and fleet typologies are needed. This is especially flagrant in the particular use case of the courier, express, parcel market, which has surged in the last few years and is the source of many inefficiencies in our neighborhoods. In this context, two-echelon networks appear as potential solutions. In these schemes, the journey of freight is divided into two distinct parts, first from the carrier’s distribution center to a network of micro-hubs and then to its final destination. Nevertheless, even if there is a reduction of the total travelled kilometers and greenhouse gas emissions, two-echelon deliveries using e-cargobikes, which is the most common model at the moment, may result in more operation costs than conventional deliveries with vans because of more complex logistics processes and higher infrastructure costs. In addition, e-cargobikes have a lower capacity, which affects their operational efficiency since more delivery routes are needed, leading to an increase of the vehicle fleet. To make two-echelon delivery schemes economically sustainable, which will eventually lead to large-scale deployments, autonomous vehicles (AVs), both ground ones and air delivery drones, seem to be promising solutions with the potential to reduce the delivery operation costs and, at the same time, the emissions of greenhouse gases. Nevertheless, the exact benefits of AVs, jointly with other technologies, such as intelligent parcel lockers, still need to be assessed at a large scale and from a holistic point of view, beyond purely operational considerations. As a consequence, in this doctoral thesis, we build a complete assessment framework for AV technologies in the context of city logistics, from planning to operations, which combines the continuous approximation methodology and a discrete optimization procedure to efficiently tackle the capacitated multi-trip vehicle routing problem with time windows and battery capacity constraints. More specifically, distinct parsimonious logistics models including the usage of air drones, ground robots and parcel lockers are built considering the characteristics of these different fleets. Moreover, a thorough life-cycle analysis is performed to quantify the environmental impact of these technologies. These different logistics models are then assessed at a large European scale and integrated with discrete optimization methods to give a holistic vision of AV operations for last-mile logistics. This doctoral thesis will help practitioners, researchers and city representatives understand the main challenges at stake with autonomous technologies from a logistics perspective, apart from the social and regulatory aspects, which are not considered. The obtained results are encouraging since the combination of a two-echelon network of delivery micro-hubs with ground autonomous delivery robots has the potential to reduce city logistics costs by around 20% in adequate conditions. Finally, externalities could also be reduced but a very particular focus should be set on the reduction of the greenhouse gas emissions from the autonomous vehicle production, to avoid observing an increase of the global warming potential on a life-cycle basis. (Català) A mesura que la millora de les operacions logístiques d’última milla es converteix en un repte cada cop més gran per les nostres ciutats, tant des d'una perspectiva econòmica com mediambiental, una àmplia mostra de noves tecnologies i esquemes de distribució innovadors estan sent testejats per les empreses logístiques i analitzats dins de la comunitat científica. Més enllà del canvi necessari en les tecnologies de propulsió, dels vehicles amb motor de combustió interna als models elèctrics, calen estratègies de lliurament i tipologies de flotes més eficients. Això és especialment flagrant en el mercat de la missatgeria, enviaments express i paqueteria, que ha augmentat en els últims anys i és l’origen de moltes ineficiències als nostres barris. En aquest context, les xarxes de distribució multinivell apareixen com a possibles solucions. En aquests esquemes, el viatge de les mercaderies es divideix en dues parts diferenciades, primer des del centre de distribució del transportista fins a una xarxa de micro-hubs i després fins al seu destí final. No obstant això, encara que hi hagi una reducció del total de quilòmetres recorreguts i de l’impacte mediambiental, els lliuraments amb bicicletes, que és el model més comú actualment, poden generar més costos d'operació per les empreses que els lliuraments convencionals amb furgonetes perquè els processos logístics són més complexos i els costos d'infraestructura més elevats. A més, les bicicletes cargo tenen una capacitat inferior, la qual cosa afecta la seva eficiència operativa, perquè es necessiten més rutes de lliurament i més vehicles per la mateixa demanda. Perquè els esquemes de lliurament binivell siguin econòmicament sostenibles, el que finalment conduirà a desplegaments a gran escala, els vehicles autònoms, tant terrestres com aeris, semblen solucions prometedores amb el potencial de reduir els costos d’operació de lliurament i, al mateix temps, les emissions de gasos d’efecte hivernacle. Tot i així, els beneficis exactes dels vehicles autònoms, juntament amb altres tecnologies, com ara les taquilles intel·ligents, encara s’han d'avaluar a gran escala i des d’un punt de vista holístic, més enllà de consideracions purament operatives. Com a conseqüència, en aquesta tesi doctoral", "keywords": [ "Greenhouse gas", "Distribution (mathematics)", "Sustainable transport", "Total cost", "Cost reduction", "Total cost of ownership", "City logistics", "Sample (material)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5821/dissertation-2117-454074" }, { "id": "https://openalex.org/W4413918908", "doi": "10.1109/icca65672.2025.11129839", "title": "Heterogeneous Alignment-Based Spatio-Temporal Graph Reinforcement Learning for Dynamic Multi-UAVs Task Assignment", "year": 2025, "publication_date": "2025-06-30", "type": "conference-paper", "language": "en", "authors": [ "Haojie Zhu", "Mou Chen", "Tongle Zhou", "Zengliang Han" ], "first_author": "Haojie Zhu", "venue": null, "publisher": null, "abstract": "The dynamic task assignment for heterogeneous Unmanned Aerial Vehicles (UAVs) has emerged as a pivotal challenge in mission-critical applications such as disaster response and urban logistics. A novel Heterogeneous Alignment-based Spatio-Temporal Graph Reinforcement Learning (HASTG-RL) framework is proposed to address this issue. First, a Dynamic Spatio-Temporal Graph (DSTG) is constructed to update environment states continuously. Second, a Transformer-based heterogeneous alignment mechanism is developed to resolve the UAV heterogeneity. Moreover, independent critic networks incorporating multi-objective optimization are designed to simultaneously evaluate task completion, energy consumption, and flight distance. The simulation results show that the proposed method demonstrates superior performance in task completion rate and better flight distance compared to state-of-the-art baselines in dynamic scenarios.", "keywords": [ "Reinforcement learning", "Computer science", "Task (project management)", "Graph", "Artificial intelligence", "Human–computer interaction", "Machine learning", "Theoretical computer science", "Engineering" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/icca65672.2025.11129839" }, { "id": "https://openalex.org/W4392668750", "doi": "10.1109/dsins60115.2023.10455630", "title": "Research on Model-Based Cooperative Delivery Problem of Trucks and UAVs", "year": 2023, "publication_date": "2023-11-10", "type": "conference-paper", "language": "en", "authors": [ "Jinchen Zhao", "Jun Lei", "Mian Ye", "Weiran Zhang", "H. Yang" ], "first_author": "Jinchen Zhao", "venue": null, "publisher": null, "abstract": "In order to address the increasing complexity of the urban logistics and distribution environment, a novel cooperative delivery model of trucks and UAVs was proposed, aiming to improve the efficiency of logistics and distribution, reduce the economic loss caused by untimely delivery, and meanwhile solve the problems of short distribution distance and insufficient range capacity in the UAV logistics industry. K-means clustering algorithm was utilized to determine the truck distribution points, and genetic algorithm was applied to solve the problem of the shortest driving distance under the cooperative distribution model. Through numerical experiments, it was verified that the proposed method featured favorable distribution performance with faster delivery speed and less time consumption. The research provided future development of urban logistics and distribution with regard to novel ideas and methods.", "keywords": [ "Truck", "Computer science", "Transport engineering", "Engineering", "Aerospace engineering" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/dsins60115.2023.10455630" }, { "id": "https://openalex.org/W7118004674", "doi": "10.1007/978-3-032-13167-6_5", "title": "Citizens' Perceptions and Acceptance of Drone Delivery Services", "year": 2026, "publication_date": "2026-01-01", "type": "conference-paper", "language": "en", "authors": [ "Madalena Pita", "Sofia Kalakou" ], "first_author": "Madalena Pita", "venue": "Lecture notes in computer science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Reputation", "Perception", "Reliability (semiconductor)", "Key (lock)", "Social media" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-032-13167-6_5" }, { "id": "https://openalex.org/W3089136847", "doi": null, "title": "CO2 Emissions of Innovative Last Mile Delivery Solutions", "year": 2020, "publication_date": "2020-08-06", "type": "other", "language": "en", "authors": [ "F. F. Egorov" ], "first_author": "F. F. Egorov", "venue": "DSpace@MIT (Massachusetts Institute of Technology)", "publisher": "Massachusetts Institute of Technology", "abstract": "This work studies the impact of innovative last mile delivery solutions on the amount of produced CO2 emissions. An innovative last mile delivery solution is defined as a truck that carries a drone and together in tandem the truck and drone deliver parcels to the set of customers. The problem of finding the optimal route to serve customers by the truck and drone tandem is known as Travelling Salesman Problem with Drone (TSPD). However, all previously developed approaches for solving TSP-D do not consider the time dependent nature of the problem when the speed of the truck is affected by traffic congestion, infrastructure constraints, etc. To address this task, the genetic algorithm for solving a time dependent TSP-D was developed. The input information for the time dependent TSP-D algorithm is derived through “Simulation of Urban Mobility\" (SUMO) software. SUMO allows realistic simulation of the various infrastructure constraints and calculation of the information required for the time dependent TSP-D algorithm. The computational experiments show that the truck and drone tandem can significantly (more than twice) shorten the delivery time in congested urban areas. The sensitivity analysis reveals that drone speed does not considerably affect delivery time or the amount of produced CO2 emissions. Ultimately this study demonstrates that using the truck and drone tandem contributes to shorter delivery time and less CO2 emissions and provides the model for assessing these benefits.", "keywords": [ "Mile", "Last mile (transportation)", "Environmental science", "Business", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/1721.1/126491" }, { "id": "https://openalex.org/W3195476881", "doi": null, "title": "Acceptance and intention to use drone delivery services in the city of Lisbon", "year": 2020, "publication_date": "2020-11-01", "type": "dissertation", "language": "en", "authors": [ "Alvarez, Jonathan Alonso Villanueva" ], "first_author": "Alvarez, Jonathan Alonso Villanueva", "venue": "Repositório do ISCTE-IUL", "publisher": null, "abstract": "The rapid growth of e-commerce and parcel delivery has made last mile deliveries less efficient over the years. Companies are aware of that and continuously try to find solutions for the last mile problem, where the need to lower the costs meets the customer satisfaction. In this context, drone delivery service appears as an innovative technology design to solve these problems. Even though its use is expanding in Europe, its awareness and acceptance in Portugal need to be addressed to plan drone deliveries in urban logistics. This work examines the acceptance and intention to use drone delivery services by consumers in the city of Lisbon. The research is based on primary data collected by a web survey answered by 314 people living in Lisbon, within Portuguese and foreigners aged between 18 to over 65 years old. Aspects like the impact of perceived benefits and concerns on attitude and intention to use are evaluated, as well as the level of awareness and the impact of variables like gender, owning a driving license and area of residency. The results of the study show that the attitude towards drone delivery has an impact on the intention to use it, depending on how people perceive the benefits and concerns. From a managerial perspective, this study serves as information sources for companies planning to invest or implement drone delivery services, as it contains valuable information regarding the factors for consumers’ acceptance.", "keywords": [ "Drone", "Engineering", "Business", "Psychology", "Advertising" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/10071/21699>." }, { "id": "https://openalex.org/W7127205542", "doi": null, "title": "Optimizing Last-Mile Deliveries with New Technology and Strategies", "year": 2024, "publication_date": "2024-01-01", "type": "dissertation", "language": "en", "authors": [ "Iivo Huopaniemi" ], "first_author": "Iivo Huopaniemi", "venue": "Theseus (Ammattikorkeakoulujen)", "publisher": null, "abstract": "The popularity of online shopping and e-commerce has skyrocketed in the recent years. This change in consumer behavior has brought forward numerous new challenges, in the context of the final mile of logistics. These challenges come especially in the form of the three dimensions of sustainability: environment, social, and economic sustainability. In order to combat these challenges, logistics companies now look for new ways of optimizing their last mile delivery (LMD) systems. This process of optimization involves new technologies and strategies, which companies are scrambling to consider, test, and implement. Newly surfaced technologies such as electric vehicles (EV), unmanned aerial vehicles (UAV), and autonomous ground vehicles (AGV), continue to show impressive potential for last mile delivery applications, while newly surfaced strategies, such as underground logistics systems (ULS), pickup points, and crowdshipping show potential for usage of new technologies in them. Together, the new technologies and strategies aim to make last mile deliveries sustainable, improving the environmental, social, and economic conditions of consumers and companies in urban areas alike.", "keywords": [ "Last mile (transportation)", "Popularity", "Context (archaeology)", "Emerging technologies", "Mile", "Process (computing)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://www.theseus.fi/handle/10024/884313" }, { "id": "https://openalex.org/W4414759696", "doi": "10.20429/amtp.2023.08", "title": "A Guide to Controlling Supply Chain Last Mile and Reverse Last-Mile Logistics: A Study of U.S. And China Small Business Enterprises", "year": 2023, "publication_date": "2023-01-01", "type": "conference-paper", "language": "en", "authors": [ "Emmanuel Finnih" ], "first_author": "Emmanuel Finnih", "venue": null, "publisher": null, "abstract": "In the United States, the last-mile logistics infrastructure is less developed, with fewer delivery services and less efficient delivery methods. China has adopted more advanced technologies such as drones and robots for last-mile delivery, while the United States has lagged behind in this area (Zhang and Zhang, 2020). Finally, in terms of delivery methods, China has adopted more efficient methods such as same-day delivery and express delivery, while the United States has been relatively slow to adopt these methods, with many retailers still relying on traditional delivery methods like ground shipping. However, the COVID-19 pandemic has accelerated the adoption of e-commerce and delivery services in the United States, and there has been a recent surge in demand for same-day and express delivery options to meet the changing needs of consumers. (Zhang and Zhang, 2020). This research will use the grounded theory approach to analyze the last-mile logistics in China and the United States, drawing on the expertise of the supply chain industry. This study will also identify patterns and potential areas of growth in both China and the United States.", "keywords": [ "China", "Supply chain", "Last mile (transportation)", "Supply chain management", "Delivery system", "Small business", "Drone", "Humanitarian Logistics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://digitalcommons.georgiasouthern.edu/cgi/viewcontent.cgi?article=1038&context=amtp-proceedings_2023" }, { "id": "https://openalex.org/W2912034696", "doi": null, "title": "BUSINESS ANALYSIS OF THE DRONE’S LAST MILE DELIVERY ENVIRONMENT", "year": 2018, "publication_date": "2018-04-11", "type": "article", "language": "en", "authors": [ "Caio Ferreira Da Rosa Pantarotto" ], "first_author": "Caio Ferreira Da Rosa Pantarotto", "venue": null, "publisher": null, "abstract": "Make an overall analysis of business models that include the use of drones on the last mile delivery developing fittable business models and proposing MILP model", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Aeronautics", "Computer science", "Business", "Engineering", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://webthesis.biblio.polito.it/7281/" }, { "id": "https://openalex.org/W7106013218", "doi": "10.25365/thesis.79578", "title": "A solution technique for the truck and drone parcel delivery problem", "year": 2025, "publication_date": "2025-01-01", "type": "dissertation", "language": "en", "authors": [ "Lidi, Márk" ], "first_author": "Lidi, Márk", "venue": "University of Vienna", "publisher": null, "abstract": "Diese Arbeit befasst sich mit den drängenden Herausforderungen des städtischen Güterverkehrs und der letzten Meile in der Europäischen Union. Insbesondere das starke Wachstum des Onlinehandels sowie die fortschreitende Urbanisierung erhöhen den Druck auf bestehende Transportinfrastrukturen. Der Straßengüterverkehr dominiert zwar weiterhin die Logistik, verursacht jedoch einen beträchtlichen Anteil an Treibhausgasemissionen, Luftschadstoffen und Verkehrsstaus (WEF, 2024; Sustainable Urban Logistics Plans, EU, 2023). Vor dem Hintergrund der europäischen Klimapolitik und ambitionierter Nachhaltigkeitsziele gewinnt daher die Entwicklung innovativer Konzepte an Bedeutung, um Transportprozesse mit den Emissionsreduktionsvorgaben in Einklang zu bringen (Levrey, 2024; Mahmoodi et al., 2025). In diesem Kontext wird ein heuristik-basierter Planungsansatz vorgestellt, der klassische Methoden der Routenoptimierung mit neuen Lieferkonzepten – darunter unbemannte Luftfahrzeuge (UAVs) und autonome Systeme – verbindet. Ziel ist es, Lieferketten so zu gestalten, dass technische Rahmenbedingungen wie begrenzte Drohnenreichweiten, Nutzlastgrenzen, Ladeinfrastruktur oder gesetzliche Flugverbotszonen berücksichtigt werden, ohne die praktische Anwendbarkeit durch übermäßige Rechenlast zu gefährden (Mahmoodi et al., 2025; Cicek et al., 2025). Die empirischen Ergebnisse verdeutlichen die Zielkonflikte zwischen Kosten, Zeitaufwand und ökologischen Effekten. Besonders in dicht besiedelten urbanen Räumen lassen sich mit kombinierten Drohnen-Lkw-Modellen die CO₂-Emissionen um bis zu 20 % im Vergleich zu rein dieselbetriebenen Lkw-Systemen senken (Bao et al., 2025). Damit liefert die Arbeit einen Beitrag zur wissenschaftlichen Debatte über nachhaltige urbane Logistik, indem sie sowohl theoretische Grundlagen als auch praxisnahe Ansätze zusammenführt. Der entwickelte Algorithmus unterstreicht das Potenzial hybrider Zustelllösungen, die den Einsatz von Drohnen mit Lkw und die Integration von E-Cargobikes kombinieren. Solche Konzepte eröffnen neue Möglichkeiten, Emissionen zu verringern und die Effizienz in der letzten Meile zu erhöhen. Über die wissenschaftliche Relevanz hinaus bieten die Erkenntnisse wertvolle Anhaltspunkte für politische Entscheidungsträger, Logistikunternehmen und Stadtverwaltungen, die auf dem Weg zu sauberen, resilienten und intelligenten städtischen Transportsystemen sind – im Einklang mit dem European Green Deal sowie den Nachhaltigkeitsstrategien der Europäischen Kommission (Levrey, 2024; Sustainable Urban Logistics Plans, EU, 2023).", "keywords": [ "Context (archaeology)", "European union", "Truck" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.25365/thesis.79578" }, { "id": "https://openalex.org/W7112027101", "doi": null, "title": "Integrated Unmanned Aerial Vehicles and Public Buses for Parcel Delivery in Urban Area", "year": 2025, "publication_date": "2025-04-25", "type": "conference-paper", "language": "en", "authors": [ "Zhen, Yizhi", "Lin, Jie", "Zhang, Fangni" ], "first_author": "Zhen, Yizhi", "venue": "The HKU Scholars Hub (University of Hong Kong)", "publisher": "University of Hong Kong", "abstract": "Deploying Unmanned Aerial Vehicles (UAVs) for parcel delivery in urban areas offers faster, more flexible, and cost-effective services while reducing traffic congestion, environmental impact, and improving accessibility. However, UAV efficiency is constrained by limited flight range and battery life, posing challenges in covering large urban areas. Leveraging the dense urban bus networks and the substantial number of buses in operation presents a novel solution: integrating UAVs with public buses. In this approach, buses act as mobile charging stations, enabling en-route UAV recharging and facilitating ride share with buses to enhance delivery efficiency. To optimize UAV routing and recharging schedules, we propose a Mixed Integer Programming (MIP) model. Due to the model’s complexity, an Adaptive Large Neighborhood Search (ALNS) heuristic algorithm is employed for efficient problem-solving. Numerical experiments on varying scales show that for small instances, our ALNS heuristic matches Gurobi's optimal solutions in less time. For larger instances, where Gurobi provides only feasible lower bounds within limited time, our ALNS heuristic delivers superior solutions faster. Real-world experiments in Shenzhen’s Luohu district further validate the effectiveness of the bus-UAV integration. Compared to UAV-only delivery, our approach reduces average costs by up to 29.53%, and by 18.18% in average compared to charging station-based en-route recharging, demonstrating significant operational advantages.", "keywords": [ "Heuristic", "Routing (electronic design automation)", "Public transport", "Urban area", "Integer programming", "Range (aeronautics)", "Drone" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hub.hku.hk/handle/10722/359473" }, { "id": "https://openalex.org/W2904725745", "doi": null, "title": "Communication Relay Applications of a Solar-powered UAV Following a Collision-free Optimal Flight Path", "year": 2018, "publication_date": "2018-10-01", "type": "article", "language": "en", "authors": [ "Giancarlo Eder Guerra Padilla", "Seong-Hwan Kim", "Kee-Ho Yu" ], "first_author": "Giancarlo Eder Guerra Padilla", "venue": null, "publisher": null, "abstract": "In the occurrence of natural disasters or any other event that causes damage to the communication system’s infrastructure of a city, logistics and rescue works tend to lack in countermeasures to assure a stable communication when needed. This study is aimed to developing a collision-free optimal flight path of a solar-powered UAV, exploiting its capability for long endurance flights, using it as a Low Altitude Platform (LAP) for communication relay. The model considers the solar incidence angle, aircraft attitude, influence of Artificial Potential Fields, and Free-space transmission signal. Apart from this considerations, a flight altitude restriction is defined and bounded to maximum antenna range. As a result of the simulation, a collision-free flight path considering antenna specifications for communication relay was tested resulting in the acquisition of significant data regarding the feasibility of the approach.", "keywords": [ "Relay", "Collision", "Aerospace engineering", "Computer science", "Transmission (telecommunications)", "Antenna (radio)", "Path (computing)", "Collision avoidance", "Range (aeronautics)", "Altitude (triangle)", "Simulation", "Engineering" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=8571719" }, { "id": "https://openalex.org/W2729125190", "doi": null, "title": "Trucking in the 21st century : the big and small of last-mile delivery : e-commerce is driving a last-mile delivery boom, with everyone from startup drone makers to big less-than-truckload operations getting in on the business", "year": 2017, "publication_date": "2017-04-01", "type": "article", "language": "en", "authors": [ "Deborah Lockridge" ], "first_author": "Deborah Lockridge", "venue": "Newport's heavy duty trucking", "publisher": null, "abstract": null, "keywords": [ "Mile", "Drone", "Boom", "Last mile (transportation)", "Aeronautics", "Business", "Engineering", "Advertising", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://trid.trb.org/view/1468963" }, { "id": "https://openalex.org/W4230916325", "doi": "10.32920/ryerson.14660943", "title": "Multimodal Automated Last-Mile Delivery System: Design and Application", "year": 2021, "publication_date": "2021-06-08", "type": "other", "language": "en", "authors": [ "Farah Samouh" ], "first_author": "Farah Samouh", "venue": null, "publisher": null, "abstract": "This thesis focuses on exploring the emerging automated technologies for last-mile on-demand food delivery as a new means of transportation to reduce congestion in urban areas. In order to achieve that 4 systems are designed and evaluated: Robot delivery system, drone delivery system and two hybrid delivery systems. Both hybrid systems are based on hub-spoke networks, Hybrid System 1.0 uses robots for phase one of the delivery and drones for phase two Hybrid System 2.0 uses drones for phase one and robots for phase two. To evaluate the efficiency of these systems, an in-house agent-based simulation model in MATLAB is developed for the City of Mississauga. 30 scenarios are tested differing in terms of demand and fleet size. The results show that Hybrid system 2.0 is the most efficient system of all four proposed due to the use of hub, customer waiting time and landing zones for drones.", "keywords": [ "Drone", "Last mile (transportation)", "Hybrid system", "Computer science", "Food delivery", "Robot", "Delivery system", "Mile", "Simulation", "Phase (matter)", "Transport engineering", "Real-time computing" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.32920/ryerson.14660943" }, { "id": "https://openalex.org/W7136155644", "doi": "10.3390/drones10030203", "title": "A Dual-Layer Optimization Framework for Multi-UAV Delivery Scheduling in Multi-Altitude Urban Airspace", "year": 2026, "publication_date": "2026-03-14", "type": "article", "language": "en", "authors": [ "Yong Wang", "Jiuye Leixin", "Dayuan Zhang", "Yuxuan Ji", "Xi Vincent Wang", "Lihui Wang" ], "first_author": "Yong Wang", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Efficient UAV logistics in complex urban airspaces requires a synergistic approach to task allocation and path planning. However, traditional methods often decouple these two phases, leading to physically infeasible or sub-optimal delivery schedules. This paper proposes a Dual-Layer Optimization Framework (D-LOF) to address the Multi-UAV delivery problem in 3D urban environments. The upper layer utilizes an improved Genetic Algorithm (GA) with a specialized constraint repair operator to optimize task sequences for a heterogeneous UAV fleet. The lower layer employs an altitude-aware A* algorithm that dynamically balances vertical energy costs and horizontal cruise efficiency across multiple altitude layers. Unlike conventional models, our framework iteratively feeds precise 3D flight costs from the lower layer back to the upper layer to guide evolutionary search. Simulation results demonstrate that the D-LOF consistently achieves global convergence within 20 generations. Compared to single-altitude planning and rule-based strategies, the proposed method can reduce total operational costs and maintains zero time-window violations in high-density obstacle scenarios. This study provides a robust decision-making tool for “last-mile” urban logistics by navigating the trade-offs between 3D spatial constraints and delivery punctuality.", "keywords": [ "Obstacle", "Scheduling (production processes)", "Convergence (economics)", "Task (project management)", "Constraint (computer-aided design)", "Path (computing)", "Motion planning", "Layer (electronics)" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/10/3/203/pdf?version=1773472705" }, { "id": "https://openalex.org/W7153290134", "doi": "10.20944/preprints202604.0751.v1", "title": "Optimal Cruise Speeds and Environmental Effects on Energy Consumption of Multirotor UAVs for Last-Mile Delivery", "year": 2026, "publication_date": "2026-04-10", "type": "preprint", "language": null, "authors": [ "Sung-Hyuk Choi" ], "first_author": "Sung-Hyuk Choi", "venue": "Preprints.org", "publisher": null, "abstract": "Unmanned aerial vehicles (UAVs) are increasingly recognized as a viable option for urban parcel delivery. However, their energy performance under varying environmental and mission conditions remains underexplored. This paper presents a simulation-based analysis of multirotor UAV energy consumption using the PX4-Gazebo platform, calibrated with real-world telemetry from a publicly available DJI Matrice 100 dataset [12]. Three UAV models—Iris, Typhoon H480, and Octocopter—were evaluated across a range of payloads (0.1–5 kg), cruise speeds (2–16 m/s), and environmental factors, including wind, temperature, and humidity. Results revealed consistent U-shaped energy speed curves, with optimal cruise speeds ranging from 8 to 10 m/s, depending on the payload and platform. Headwinds alone increased energy consumption by up to 25% and combined cold–dry and headwind conditions resulted in increases of up to 53% for lightweight platforms. Validation against field telemetry showed mean absolute percentage errors below 11%. These findings offer a simulation-grounded framework for UAV mission planning, platform selection, and integration into energy-efficient logistics networks, and development of data-driven optimization frameworks. The three platforms span a 10-fold mass range (1.4–14 kg), enabling systematic analysis of how energy scaling behavior varies across lightweight, mid-range, and heavy-lift delivery configurations.", "keywords": [ "Multirotor", "Cruise", "Energy consumption", "Payload (computing)", "Telemetry", "Range (aeronautics)", "Energy (signal processing)", "Fuel efficiency" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.preprints.org/frontend/manuscript/0d9353def3f045117ab4d933a2fb2797/download_pub" }, { "id": "https://openalex.org/W3110378170", "doi": null, "title": "Scheduling and route planning of unmanned aerial vehicle for multi-parcel postal delivery in Singapore", "year": 2020, "publication_date": "2020-01-01", "type": "report", "language": "en", "authors": [ "Germaine Jia Min Ee" ], "first_author": "Germaine Jia Min Ee", "venue": "DR-NTU (Nanyang Technological University)", "publisher": "Nanyang Technological University", "abstract": "With rising popularity in online shopping, volume of parcels in Singapore has been increasing at an average of 14% every year and this trend is expected to continue for the upcoming years. In 2017 and 2018, Singpost has been fined for failure to meet delivery demand as it struggles to cope with the rising demand for home delivery. An alternative solution is needed to increase the manpower to cope with the current and future demand. Hence, UAV was introduced to increase the manpower capacity, especially in delivering lightweight parcels. As there are limitations on the total weight carried by UAV and the flight time of a UAV, it is important to maximise these constraints for efficient delivery using UAV. Hence, multi-parcel delivery by UAV was introduced. In a multi-parcel delivery by UAV, packing of parcels and planning of route are required to achieve optimisation in the above constraints. Yet, many research on multi- parcel delivery only focus on route planning to find the shortest route. Furthermore, many studies on scheduling only considered optimisation with weight limitation. Therefore, this project aims to develop a delivery system that focus on both scheduling and route planning, where there is a limitation on the number of items and total weight each UAV can carry in a trip during scheduling. The process flow of the UAV delivery system were discussed. Mathematical model and algorithm on scheduling and routing planning were developed. Power consumption of UAV was also modelled as a linear regression line. Results showed that delivery by UAV was optimised. There was also a minimal difference of 2% between the linear regression line and the power equation. The delivery system has also achieved a significant reduction in time and cost with at least 20% improvement as compared to the current delivery system. Therefore, a feasible multi-parcel UAV delivery system in Singapore was achieved.", "keywords": [ "Scheduling (production processes)", "Computer science", "Transport engineering", "Operations research", "Aeronautics", "Operations management", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/10356/141261" }, { "id": "https://openalex.org/W2291528532", "doi": "10.1109/aero.2016.7500543", "title": "MPC controlled multirotor with suspended slung Load: System architecture and visual load detection", "year": 2016, "publication_date": "2016-03-01", "type": "conference-paper", "language": "en", "authors": [ "Markus Zurn", "Kye Morton", "Alexander Heckmann", "Aaron McFadyen", "Stefan Notter", "Felipé Gonzalez" ], "first_author": "Markus Zurn", "venue": null, "publisher": null, "abstract": "There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (∼5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.", "keywords": [ "Multirotor", "Computer science", "Real-time computing", "Offset (computer science)", "Controller (irrigation)", "Position (finance)", "Simulation", "Trajectory", "Control theory (sociology)", "Control engineering", "Artificial intelligence", "Engineering" ], "cited_by_count": 22, "is_retracted": false, "is_paratext": false, "open_access_url": "https://eprints.qut.edu.au/92313/1/MPC_controlled_Multirotor_with_suspended_slung_Load_System_Architecture_and_Visual_Load_Detection_finalV2.pdf" }, { "id": "https://openalex.org/W7167907687", "doi": "10.1016/j.tra.2026.105144", "title": "Cooperative drone-based hitchhiking vehicle framework for last-mile logistics services: A case study for online food delivery scenarios", "year": 2026, "publication_date": "2026-07-10", "type": "article", "language": "en", "authors": [ "Zijian Ding", "Fan Zhang", "Wei Ma" ], "first_author": "Zijian Ding", "venue": "Transportation Research Part A Policy and Practice", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Vehicle routing problem", "Key (lock)", "Food delivery", "Supply chain", "Public transport" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tra.2026.105144" }, { "id": "https://openalex.org/W4231495250", "doi": "10.32920/ryerson.14660943.v1", "title": "Multimodal Automated Last-Mile Delivery System: Design and Application", "year": 2021, "publication_date": "2021-06-08", "type": "other", "language": "en", "authors": [ "Farah Samouh" ], "first_author": "Farah Samouh", "venue": null, "publisher": null, "abstract": "This thesis focuses on exploring the emerging automated technologies for last-mile on-demand food delivery as a new means of transportation to reduce congestion in urban areas. In order to achieve that 4 systems are designed and evaluated: Robot delivery system, drone delivery system and two hybrid delivery systems. Both hybrid systems are based on hub-spoke networks, Hybrid System 1.0 uses robots for phase one of the delivery and drones for phase two Hybrid System 2.0 uses drones for phase one and robots for phase two. To evaluate the efficiency of these systems, an in-house agent-based simulation model in MATLAB is developed for the City of Mississauga. 30 scenarios are tested differing in terms of demand and fleet size. The results show that Hybrid system 2.0 is the most efficient system of all four proposed due to the use of hub, customer waiting time and landing zones for drones.", "keywords": [ "Drone", "Last mile (transportation)", "Hybrid system", "Computer science", "Food delivery", "Robot", "Delivery system", "Mile", "Real-time computing", "Transport engineering", "Simulation", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://rshare.library.ryerson.ca/articles/thesis/Multimodal_Automated_Last-Mile_Delivery_System_Design_and_Application/14660943/1/files/28143447.pdf" }, { "id": "https://openalex.org/W7133412880", "doi": null, "title": "Solution to the multi-echelon vehicle routing problem considering time windows and drones in the last mile delivery for the management of humanitarian operations", "year": 2023, "publication_date": "2023-02-28", "type": "dissertation", "language": "es", "authors": [ "Jennifer María Cataño Albarracín" ], "first_author": "Jennifer María Cataño Albarracín", "venue": "Universidad Industrial de Santander", "publisher": null, "abstract": "Este documento presenta un modelo matemático basado en el problema de ruteo de vehículos con drones, considerando el estudio de dos escalones y ventanas de tiempo, conocido en la literatura como el 2E-VRPD+TW (Two Echelon Vehicle Routing Problem with Drones + Time Windows), como herramienta para facilitar la toma de decisiones durante las etapas de preparación y respuesta en la gestión de desastres, específicamente en operaciones de entrega de suministros en áreas afectadas por desastres naturales; teniendo como objetivo la minimización del costo total de operación. Para representar el problema abordado, se hace uso de la programación lineal, utilizando como técnica de solución al algoritmo genético (Genetic Algorithm, GA) en su versión general y paralela. El algoritmo genético implementa la heurística del vecino más cercano en el ruteo de los drones y un método aleatorio en el de los vehículos, al ser validado demuestra adaptarse bien al problema, ofreciendo resultados lógicos y coherentes. El análisis estadístico de los resultados obtenidos muestra que el factor con mayor influencia sobre el costo total y el tiempo computacional es el número de generaciones y que la implementación del paralelismo mejora los resultados obtenidos. Finalmente se hacen recomendaciones para futuras investigaciones.", "keywords": [ "Drone", "Routing (electronic design automation)", "Internet of Things", "Work (physics)", "Vehicle routing problem" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://noesis.uis.edu.co/bitstreams/a26635f5-743d-4e78-b311-329496f9854a/download" }, { "id": "https://openalex.org/W7160997210", "doi": "10.31004/jutin.v9i1.55995", "title": "Integrasi Analisis Bibliometrik Scopus–VOSviewer dan Simulasi Diskrit (ProModel) dalam Evaluasi Kinerja Distribusi Drone Last-Mile", "year": 2026, "publication_date": "2026-01-20", "type": "article", "language": null, "authors": [ "Ok Rangga Ahyar", "Putri Parinduri", "Rahmat Fadhillah", "Syarifuddin Solin", "Khairul Nizan Aulia" ], "first_author": "Ok Rangga Ahyar", "venue": "Jurnal Teknik Industri Terintegrasi", "publisher": "Universitas Pahlawan Tuanku Tambusai", "abstract": "The results of the co-occurrence, co-authorship, and citation analyses indicate that existing studies predominantly emphasize technical development, artificial intelligence integration, communication systems, and sustainability aspects, while quantitative operational performance modeling remains limited. Based on the identified research gaps, a discrete event simulation model was developed in promodel to represent operational processes, including order reception, routing, loading, flight operations, battery charging or swapping, and return cycles. Several policy scenarios were tested by varying fleet size, charging station capacity, and demand patterns. Simulation results demonstrate that system performance is significantly influenced by charging infrastructure capacity, resource allocation, and scheduling configuration, directly affecting delivery time, throughput, and drone utilization. The integration of bibliometric mapping and simulation modeling provides a comprehensive decision-support framework that bridges conceptual research trends with practical operational optimization in last-mile drone logistics.", "keywords": [ "Drone", "Scheduling (production processes)", "Discrete event simulation", "Conceptual model", "Resource (disambiguation)", "Resource allocation" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://journal.universitaspahlawan.ac.id/index.php/jutin/article/download/55995/33694" }, { "id": "https://openalex.org/W7103989003", "doi": "10.5281/zenodo.17522385", "title": "Study of Swarming Logistics with Tactical Last Mile Delivery", "year": 2025, "publication_date": "2025-11-04", "type": "article", "language": null, "authors": [ "Maj Nilam Gorwade", "Dr. John A" ], "first_author": "Maj Nilam Gorwade", "venue": "International Journal of Scientific Research and Engineering Trends", "publisher": null, "abstract": "Last-mile delivery in a military context can often be dangerous, putting personnel and the supplies they carry at risk. The emergence of aerial ‘delivery drones’ from the commercial delivery sector highlights the possibilities of uncrewed vehicles being used in last-mile delivery. However, demonstrations of such technology have been limited to single vehicle deliveries, where only small portions of supplies can be delivered at once. This paper explores the concept of low-cost, uncrewed vehicle swarming for tactical last-mile delivery in a deployed setting. The benefits of uncrewed swarming systems over conventional methods of resupply are discussed, as well as the vulnerabilities and challenges faced by such systems.", "keywords": [ "Swarming (honey bee)", "Drone", "Context (archaeology)", "Delivery system", "Last mile (transportation)", "Paratransit" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.17522385" }, { "id": "https://openalex.org/W7117627602", "doi": "10.1109/mswim67937.2025.11308755", "title": "dynRDF: Using Deep Contextual Bandits to Optimize Position Flooding in Urban UAV Networks", "year": 2025, "publication_date": "2025-10-27", "type": "conference-paper", "language": null, "authors": [ "Konrad Fuger", "Kwame Ofori", "Andreas Timm‐Giel" ], "first_author": "Konrad Fuger", "venue": null, "publisher": null, "abstract": "Advances in mechanical capabilities and mass manufacturing of Unmanned Aerial Vehicles (UAVs) are driving their application in various fields from precision agriculture to infrastructure monitoring and on-demand parcel delivery. Especially in urban areas it is projected that large amount of UAVs will inhabit the airspace. To facilitate the safe and reliable operation of large-scale urban UAV deployments, an Unmanned Aerial Traffic Management (UTM) system is required. Such a system needs to be aware of all movements within the airspace to control and monitor urban UAV operations. One way to realize this is the establishment of an ad-hoc network, which UAVs use for network-wide dissemination of their positions. Recently, Rate Decay Flooding (RDF) has been proposed as a tailor-made protocol to realize such a system. Although RDF has been proven to be efficient in supporting UTM applications in larger networks than ordinarily possible, much of its success relies on the proper selection of protocol parameters. In this work, we propose a reinforcement-learning framework that automatically adapts the configuration of RDF to its perceived environment. We utilize deep contextual bandits as a light-weight, but effective method to capture the non-linear relationship between the perceived environment and the achieved performance. We name this extension Dynamic Rate Decay Flooding (dynRDF). In a simulation study, we show that this solution is effective in finding optimal configurations for RDF for varying network sizes. To achieve this, only 2.7 % of all possible configurations had to be explored. Allowing dynRDF to also take the local UAV density into account, a performance gain of more than 12 % is achieved in a relevant composite metric capturing both the timely dissemination of position updates to nearby UAVs and reliable network-wide dissemination.", "keywords": [ "Flooding (psychology)", "Protocol (science)", "Position (finance)", "RDF", "Scheme (mathematics)", "Control (management)" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/mswim67937.2025.11308755" }, { "id": "https://openalex.org/W3135593703", "doi": null, "title": "A study of optimized pricing models for drone-based postal delivery", "year": 2018, "publication_date": "2018-01-01", "type": "report", "language": "en", "authors": [ "Prashant Trivedi" ], "first_author": "Prashant Trivedi", "venue": "DR-NTU (Nanyang Technological University)", "publisher": "Nanyang Technological University", "abstract": "Unmanned Aerial Vehicles (UAV), more commonly known as drones, are the next disruptive robotic platforms which are meant to dive into wide range of industries. It is important that implementation and regulation of such technologies takes up to same place as the technology itself. Hence, this report examines the study of optimized pricing model of drone-based postal delivery. K-means clustering along with Newton’s method forms the basis of models, with an aim to achieve high optimization with respect to cos and number of deliveries per drone. Both models assume delivery of light weight posts through one truck and a fleet of drones. These models are largely based for Singapore’s demographics.", "keywords": [ "Drone", "Postal service", "Computer science", "Business", "Political science" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/10356/75463" }, { "id": "https://openalex.org/W7104056510", "doi": "10.5281/zenodo.17522384", "title": "Study of Swarming Logistics with Tactical Last Mile Delivery", "year": 2025, "publication_date": "2025-11-04", "type": "article", "language": null, "authors": [ "Maj Nilam Gorwade", "Dr. John A" ], "first_author": "Maj Nilam Gorwade", "venue": "International Journal of Scientific Research and Engineering Trends", "publisher": null, "abstract": "Last-mile delivery in a military context can often be dangerous, putting personnel and the supplies they carry at risk. The emergence of aerial ‘delivery drones’ from the commercial delivery sector highlights the possibilities of uncrewed vehicles being used in last-mile delivery. However, demonstrations of such technology have been limited to single vehicle deliveries, where only small portions of supplies can be delivered at once. This paper explores the concept of low-cost, uncrewed vehicle swarming for tactical last-mile delivery in a deployed setting. The benefits of uncrewed swarming systems over conventional methods of resupply are discussed, as well as the vulnerabilities and challenges faced by such systems.", "keywords": [ "Swarming (honey bee)", "Drone", "Context (archaeology)", "Delivery system", "Last mile (transportation)", "Paratransit" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.17522384" }, { "id": "https://openalex.org/W4409023578", "doi": "10.1007/978-3-031-87376-8_12", "title": "Evaluation of the Alternative Technologies for Last Mile Delivery of Small Parcels in e-Commerce", "year": 2025, "publication_date": "2025-01-01", "type": "conference-paper", "language": "en", "authors": [ "Stanislav Svichynskyi", "Olha Svichynska", "Oleksandra Shymko" ], "first_author": "Stanislav Svichynskyi", "venue": "Lecture notes in networks and systems", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Mile", "Last mile (transportation)", "Business", "Geography", "Geodesy" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-87376-8_12" }, { "id": "https://openalex.org/W7154628004", "doi": "10.17961/jdmr.28.02.202504.21", "title": "Commercialization Strategy for Customized Drone Delivery in Tourist Areas under the K-Drone Delivery Model: A Case Study of Ulju-gun", "year": 2025, "publication_date": "2025-04-30", "type": "article", "language": "en", "authors": [ "So-Ra Baek" ], "first_author": "So-Ra Baek", "venue": "Journal of Distribution and Management Research", "publisher": null, "abstract": "Purpose: This study aims to present commercialization strategies by analyzing the drone delivery pilot project in Ulju-gun, focusing on the construction of a customized drone delivery network tailored to tourist destinations and the development of efficient logistics operation strategies. Through this analysis, the study explores how drone delivery can be integrated with local distribution networks to establish a sustainable logistics system. Research design, data, and methodology: This study outlines the process of building drone delivery infrastructure and establishing a delivery network in Ulju-gun. It also explains the development of logistics operation models and product selection procedures. Based on empirical data such as delivery distance, delivery time, and order patterns, the study analyzes operational performance and derives commercialization strategies from the perspectives of logistics, operations, and regional collaboration. Results: The study confirms that drone delivery can serve as an effective alter- native in mountainous tourist destinations and other areas with limited vehicle access. In such regions, order volumes tend to concentrate during specific time periods, requiring flexible operational strategies to accommodate fluctuating demand. For successful commercialization, integrated logistics operations —including inventory management, product selection, and packaging standardization—are essential. Moreover, collaboration with local stores can improve logistics efficiency and contribute to revitalizing the local economy. Implications: Drone delivery demonstrates strong potential as a real-time last-mile service connecting tourists with products in regions with limited distribution access. It shows promise for evolving into a smart supply chain management model tailored to tourist destinations and highlights its value as a service tool to enhance tourist convenience. Furthermore, the study empha- sizes that delivery hubs can be developed into integrated hubs that link tour- ism and local commerce, beyond merely serving as logistics bases.", "keywords": [ "Drone", "Commercialization", "Tourism", "Tourist industry" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.17961/jdmr.28.02.202504.21" }, { "id": "https://openalex.org/W7128702315", "doi": "10.4018/979-8-3373-3997-9.ch001", "title": "The Impact of Last-Mile Delivery Systems on Biodiversity In Urban Areas", "year": 2026, "publication_date": "2026-02-12", "type": "book-chapter", "language": "ng", "authors": [ "Ankita Nayak", "Ipseeta Satpathy", "Sandeep Poddar" ], "first_author": "Ankita Nayak", "venue": null, "publisher": null, "abstract": "The growth of e-commerce and last-mile delivery systems, while improving retail logistics, has detrimentally impacted urban biodiversity. This is primarily due to increased land use for infrastructure and warehouses, emissions from fossil-fuel vehicles, noise pollution, and ecosystem disruptions. The reliance on trucks, excessive packaging, and poor urban planning fragments habitats, leading to declines in urban wildlife. Solutions such as electric vehicles, bike and drone deliveries, centralized pick-up lockers, and green initiatives are being explored. The research concludes that a rapid shift to more sustainable last-mile delivery methods is crucial for urban progress and environmental protection", "keywords": [ "Drone", "Urban planning", "Urban ecosystem", "Biodiversity", "Green infrastructure", "Ecosystem services", "Land-use planning", "Sustainability" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.4018/979-8-3373-3997-9.ch001" }, { "id": "https://openalex.org/W4408648097", "doi": "10.54097/yekawt61", "title": "Feasibility Study of Drone Delivery: Taking Meituan as an Example", "year": 2025, "publication_date": "2025-03-19", "type": "article", "language": "en", "authors": [ "Yuhan Shi" ], "first_author": "Yuhan Shi", "venue": "Journal of Education Humanities and Social Sciences", "publisher": null, "abstract": "With the development of technology and the growth of consumer demand, drone delivery has gradually become a research hotspot in the field of logistics. Utilizing the case of Meituan's drone delivery service as a exemplar, the present study delves into the utilization of drone delivery within the sphere of urban low-altitude logistics. It meticulously examines the technical merits, operational impediments, and the repercussions of this innovative mode of conveyance on the conventional distribution sector. Investigations indicate that the deployment of drone delivery systems is capable of effectively addressing the \"last mile\" distribution challenge within urban environments, enhancing the efficiency of logistics operations, diminishing associated costs, and affording consumers an enhanced level of convenience in their service experience.Nevertheless, the deployment of drone delivery continues to encounter a multitude of challenges encompassing technological constraints, regulatory hurdles, economic expenditures, and societal acceptance. The present article performs a comprehensive examination of various aspects within the domain of drone delivery, thereby offering valuable insights into the viability of this mode of delivery.", "keywords": [ "Drone", "Aeronautics", "Computer science", "Engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.54097/yekawt61" }, { "id": "https://openalex.org/W4367055578", "doi": "10.4324/9781003415725-53", "title": "Identification and Extraction of Retailer's Expectations in the Last-Mile Delivery", "year": 2023, "publication_date": "2023-04-26", "type": "book-chapter", "language": "en", "authors": [ "Krishna Veer Tiwari", "Leela Rani V", "Satyendra Kumar Sharma" ], "first_author": "Krishna Veer Tiwari", "venue": null, "publisher": null, "abstract": "In today’s competitive environment, as customers generate a high demand for products, retailers/manufacturers face additional pressure to meet the dynamic nature of customer demand in a sustainable manner. Last-mile delivery (LMD) is the last leg of the process and is an essential part of the delivery process. Various techniques in the past decade have come up with innovative solutions to optimize the LMD, like the Internet of Things (IoT), Machine learning (ML), autonomous vehicles, parcel lockers, and drone-based delivery, some of which are currently being implemented in industries to improve existing practices. The study involves an extensive review of literature to identify the evolution of retailer’s expectations, including the role of sustainability aspect to meet the Sustainable Development Goals (SDGs) in future delivery models. The literature is synthesized based on the methods adopted, definitions given over the years, and foundational or innovative solutions used. Using keyword cluster analysis and the software VOSviewer, the study highlighted the main enablers of evolving trends in LMD from the standpoint of different stakeholders, such as retailers, and their respective expectations. We compare the results to the present SDGs and group the findings into technology, infrastructure, and society as the three most important drivers. By identifying the research gaps, we propose the future implications for LMD that the focus should be on a specific location-based optimization technique. The value addition of the study is in the form of a comprehensive summary of three decades of literature in LMD from the perspective of the retailer and the investigation of the evolutionary trends.", "keywords": [ "Mile", "Last mile (transportation)", "Identification (biology)", "Extraction (chemistry)", "Business", "Geography", "Chromatography", "Chemistry", "Geodesy" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.4324/9781003415725-53" }, { "id": "https://openalex.org/W4416145302", "doi": "10.2139/ssrn.5737889", "title": "Optimization of Last-Mile Logistics Delivery Routes for Ground-Vehicle and Drone Parallel Distribution from Pre-Warehouses Considering Customer Priorities", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": null, "authors": [ "Zuning Zhang", "Hui Wang", "Lingxuan Liu", "Zhongjin Wang", "Xiaohan Liu", "Jie Tian" ], "first_author": "Zuning Zhang", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Distribution (mathematics)", "Key (lock)", "Distribution center" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5737889" }, { "id": "https://openalex.org/W7162671343", "doi": "10.1016/j.tra.2026.105071", "title": "A welfare-based evaluation framework for UAVs in last-mile delivery: economic assessment and roadmap design", "year": 2026, "publication_date": "2026-05-28", "type": "article", "language": "en", "authors": [ "Xing Yao", "Yaru Li", "Chunan Wang", "Bowen Yi", "Ying Fan" ], "first_author": "Xing Yao", "venue": "Transportation Research Part A Policy and Practice", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Economic impact analysis", "Risk assessment", "Technology assessment", "Impact assessment", "Economic analysis", "Health assessment" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tra.2026.105071" }, { "id": "https://openalex.org/W7168415536", "doi": "10.1016/j.trpro.2026.04.134", "title": "Integrating Autonomous Last-mile Deliveries with Public Transit", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": "en", "authors": [ "Aditya Kumar", "Lokesh Kumar Kalahasthi", "Prajwal Gudadoor", "Abhishek Abhishek", "Iván Sánchez-Díaz" ], "first_author": "Aditya Kumar", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "Lately, research has shown the potential of automation in freight transport by reducing energy consumption, emissions, noise, and operating costs—often focused exclusively on either freight (e.g., robots and drones) or passenger (e.g., automobiles and buses) transport. Hence, this research investigates the potential of technological advancements in self-driving and connected vehicles for better coordination between freight and passenger vehicles. To achieve the objective of integrating robotic last-mile deliveries with autonomous minibuses, Chalmers University in Sweden has been chosen as a case study. Pilot tests were conducted to measure the travel, handling, boarding and alighting times, and energy consumption for robots and the minibus. Freight and passenger demand were obtained from the historical daily demand data. Several scenarios for routing and bus stop locations were examined for the energy efficiency of freight deliveries via electric pickup trucks. The minibus required around 34 daily trips, operating two to three buses during peak times. The results demonstrated that robots exhibited superior energy efficiency at lower demand levels, while integrating with minibuses led to a further reduction in energy use by 20-50%. Two-way minibus movement maximised the overlapping of routes between the robot and the minibus, reducing passenger travel time; however, with an increase in the bus kilometres travelled. To reap maximum benefits of integration, it is vital to prepare an optimal plan considering the demand, vehicle size, routing, and bus stops to overlap with freight destinations.", "keywords": [ "Energy consumption", "Automation", "Robot", "Routing (electronic design automation)", "Public transport", "Transit (satellite)", "Plan (archaeology)", "Fuel efficiency" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2352146526003960/pdf" }, { "id": "https://openalex.org/W7213446938", "doi": "10.1287/msom.2024.1197", "title": "Last-Mile Humanitarian Logistics Planning with Isolated Communities", "year": 2026, "publication_date": "2026-09-17", "type": "article", "language": "en", "authors": [ "Mahdi Noorizadegan", "Mohammad Fattahi", "Esmaeil Keyvanshokooh", "Jon M. Stauffer" ], "first_author": "Mahdi Noorizadegan", "venue": "Manufacturing & Service Operations Management", "publisher": "Institute for Operations Research and the Management Sciences", "abstract": "Problem Definition: This paper addresses the critical challenge of delivering humanitarian aid to points of distribution (PoDs) after a disaster under uncertainty, particularly when some PoDs become isolated due to road/bridge damages. Motivated by the Eta and Iota hurricanes in Honduras, we introduce a new Last-mile Humanitarian Logistics Planning problem that jointly determines: the location and capacity of staging areas (SAs), the fleet-sizes of heterogeneous mobile units-ground and aerial, the allocation of mobile units to SAs, and routing decisions ensuring all PoDs are served within a target delivery time. Mobile units can perform multiple trips within this window, enabling efficient fleet-size optimization. Methodology/Results: We formulate this problem as a Parallel Drone–Vehicle Routing Problem with Location and Fleet-Size Decisions, modeled as a route-based mixed-integer program that captures uncertainty in demand and travel times via a unified chance constraint framework. This framework accommodates multiple uncertainty modeling approaches—standard chance-constraints, CVaR-based constraints, and distributionally robust chance-constraints along with a deterministic benchmark, allowing decision-makers to control robustness levels under varying data availability. To solve this complex problem exactly, we develop a tailored Branch-and-Price algorithm, where the nonlinear pricing subproblem is reformulated as a Shortest-Path Problem with Chance-Constraints, efficiently solved by a customized dynamic programming approach with new dominance conditions. Notably, the complexity of the uncertainty model remains comparable to the deterministic counterpart, making our approach practical and scalable. Managerial Implications: A case study and synthetic instances demonstrate our framework’s versatility and practical relevance. Our results uncover critical trade-offs between robustness and investment, the effects of delivery time targets and isolation on network structure and fleet-size, and differences across uncertainty-modeling approaches. They also highlight the role of aerial fleet composition on operational efficiency and economic performance. These analyses provide actionable guidance on network configuration, fleet-sizing, and preferred modeling approaches under limited data and resources typically seen in humanitarian response.", "keywords": [ "Robustness (evolution)", "Robust optimization", "Humanitarian Logistics", "TRIPS architecture", "Vehicle routing problem", "Facility location problem", "Stackelberg competition", "Column generation", "Humanitarian aid", "Routing (electronic design automation)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1287/msom.2024.1197" }, { "id": "https://openalex.org/W4402700196", "doi": "10.1007/978-981-97-6748-9_1", "title": "Enhancing Urban Logistics Through Integrated Public Transit Vehicles and Unmanned Aerial Vehicles", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Shaohua Cui", "Jelena Anric", "Yongjie Xue", "Ruo Jia" ], "first_author": "Shaohua Cui", "venue": "Smart innovation, systems and technologies", "publisher": "Springer Nature", "abstract": null, "keywords": [ "Transit (satellite)", "Public transport", "Transport engineering", "Aeronautics", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-981-97-6748-9_1" }, { "id": "https://openalex.org/W7148733859", "doi": "10.1371/journal.pone.0345778", "title": "VLM-Nav: Mapless UAV navigation using monocular vision driven by vision-language models", "year": 2026, "publication_date": "2026-04-03", "type": "article", "language": "en", "authors": [ "Gobinda Chandra Sarker", "AKM Azad", "Sejuti Rahman", "Md Mehedi Hasan" ], "first_author": "Gobinda Chandra Sarker", "venue": "PLoS ONE", "publisher": "Public Library of Science", "abstract": "Autonomous vehicles, such as Unmanned Aerial Vehicles (UAVs), have the potential to completely reshape various industries such as parcel delivery, agriculture, surveillance, monitoring, and search-and-rescue missions. Consequently, the demand for safe, cost-effective, and intelligent navigation systems is crucial to ensure reliable performance in complex and dynamic environments. In this study, we propose a novel vision-based UAV navigation method that integrates depthmap estimation with a Vision-Language Model (VLM) for efficient obstacle avoidance and path planning. The system processes RGB images captured by the UAV, transforming them into depth maps using DepthAnything-V2, a powerful zero-shot depth estimator. These depth maps are then analyzed by the VLM, which detects nearby obstacles and plans avoidance maneuvers. We have explored the Gemini-flash and GPT-4o models as VLM in our study. A fully connected network integrates the VLM output with the UAV's relative heading angle to predict the optimal course of action, enabling the UAV to dynamically navigate complex environments toward its target. The system's effectiveness is validated through simulations in AirSim using Blocks and the Downtown West environment. The UAV consistently reaches its destination, avoiding obstacles and achieving a near-perfect task completion rate of 0.98. By eliminating the need for costly sensors such as LiDAR and operating without pre-existing maps, our solution provides a cost-efficient, generalizable approach to real-time UAV navigation, especially in unfamiliar or dynamic settings, and highlights emerging trends in autonomous systems research that utilize VLMs.", "keywords": [ "Obstacle avoidance", "Heading (navigation)", "Obstacle", "Monocular", "Task (project management)", "Lidar", "Trajectory", "Monocular vision", "Path (computing)", "Global Positioning System" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0345778&type=printable" }, { "id": "https://openalex.org/W7204895910", "doi": "10.3390/engproc2026154013", "title": "Hierarchical Security Framework for Drone Control in Parcel Delivery", "year": 2026, "publication_date": "2026-08-31", "type": "conference-paper", "language": null, "authors": [ "Ivan D. Ivanov", "Filip Atanasov Tsvetanov" ], "first_author": "Ivan D. Ivanov", "venue": null, "publisher": null, "abstract": "Secure delivery of packages by drones requires reliable management of cryptographic keys, despite limited on-board resources, multiple users, and the risk of interception or manipulation. This paper proposes a hierarchical model of a Key Distribution Center that manages the generation, distribution, storage, control, and destruction of cryptographic keys. The model uses public-key mechanisms for secure transmission of session keys and lightweight symmetric encryption for communication between the drone and the recipient. A session key lifecycle is defined, including verification, encrypted storage, validity control, and secure deletion. The operational workflow for the secure delivery of packages is also described. The proposed approach improves confidentiality, scalability, and access control.", "keywords": [ "Drone", "Encryption", "Key management", "Cryptography", "Key (lock)", "Access control", "Workflow", "Session (web analytics)", "Cryptographic protocol" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3390/engproc2026154013" }, { "id": "https://openalex.org/W7208807344", "doi": "10.5281/zenodo.22297604", "title": "When truck-paired drones save time and energy: capability interactions and a power-ratio boundary in last-mile delivery (solver + experiments)", "year": 2026, "publication_date": "2026-09-04", "type": "software", "language": "en", "authors": [ "Yifu Zhao", "Xiaofan Zou", "Junhao Wei", "Yanxiao Li", "Haochen Li", "Baili Lu", "Sio‐Kei Im", "Yapeng Wang", "Xu Yang" ], "first_author": "Yifu Zhao", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Reproducibility release for the Scientific Reports manuscript “When truck-paired drones save time and energy: capability interactions and a power-ratio boundary in last-mile delivery.” The archive contains the truck–drone routing solver, exact and diagnostic validation code, experiment and analysis drivers, pinned Python and Julia environments, cached road-network inputs, all retained seed-level results and routes, checkpoints, revision figures, protocol and deviation records, a release manifest, and per-file SHA-256 checksums. It supports the reported capability-interaction, operational-sensitivity, time–energy boundary, fixed-density, comparator, and road-geometry analyses. Larger-instance solutions are heuristic estimates and carry no optimality or near-optimality claim.", "keywords": [ "Drone", "Boundary (topology)", "Python (programming language)", "Heuristic", "Protocol (science)", "Reproducibility" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.22297604" }, { "id": "https://openalex.org/W7163918265", "doi": "10.32702/2307-2105.2026.5.115", "title": "ІННОВАЦІЙНІ РІШЕННЯ В ЛОГІСТИЦІ «LAST-MILE DELIVERY»", "year": 2026, "publication_date": "2026-05-26", "type": "article", "language": null, "authors": [ "Д.І. Басюк", "В.В. Давиденко", "О. Г. Басюк" ], "first_author": "Д.І. Басюк", "venue": "Efektyvna ekonomika", "publisher": "DKS Center", "abstract": "У статті проаналізовано сутність поняття «логістика останньої милі» (last-mile delivery) як ключового етапу сучасних ланцюгів постачань, на якому забезпечується безпосередня взаємодія з кінцевим споживачем та формується загальне сприйняття ефективності логістичної системи.Цей компонент постачального процесу вирізняється підвищеною складністю через урбаністичну щільність забудови, варіативність транспортних потоків у міських агломераціях, підвищені очікування клієнтів стосовно оперативності й персоналізації послуги, а також трансформацію споживчих практик під впливом розвитку електронної комерції.Сучасні споживачі орієнтовані не лише на базову доставку, а на високотехнологічний сервіс миттєвого доступу, що передбачає точне дотримання часових рамок, наявність альтернативних пунктів видачі та мінімізацію фізичного контакту.Водночас зростає регуляторний тиск щодо екологічної відповідальності, зокрема через обмеження емісій у центральних міських зонах, імперативи сталого транспортного забезпечення та впровадження зон із нульовими викидами, які стають стандартом у провідних країнах.Міжнародний досвід свідчить про еволюцію до кардинальних інноваційних підходів, серед яких автономні безпілотні літальні апарати, автоматизовані поштові термінали, мікrologістичні сховища в житлових масивах та алгоритми штучного інтелекту для динамічної оптимізації транспортних маршрутів.В українському контексті релевантність проблеми посилюється специфікою внутрішнього ринку, де спостерігається прискорений розвиток онлайн-торгівлі на тлі інфраструктурних обмежень, логістичних загроз, зумовлених безпековими чинниками, та нагальної потреби в економічній ревіталізації післявоєнного періоду.Вітчизняні логістичні оператори опинилися перед викликами дефіциту автоматизованих логістичних вузлів, кадрового забезпечення та розробки гнучких форм співробітництва.Дослідження інноваційних підходів у логістиці останньої милі набуває фундаментального значення для конструювання стратегій сталого розвитку.Воно створює передумови не тільки для запозичення апробованих глобальних практик, але й для їхньої адаптації до локальних реалій з формування гібридних моделей, які інтегрують передові технологічні вектори (Інтернет речей, блокчейн-технології, штучний інтелект) з національними пріоритетами екологічної модернізації.This article analyses the concept of 'last-mile delivery' as a key stage in modern supply chains, during which direct interaction with the end consumer takes place and the overall perception of the logistics system's efficiency is formed.This component of the supply process is characterised by increased complexity due to the density of urban development, the variability of traffic flows in urban agglomerations, heightened customer expectations regarding the speed and personalisation of the service, as well as the transformation of consumer practices under the influence of the development of e-commerce.Modern consumers are focused not only on basic delivery, but on a hightech instant-access service that requires strict adherence to timeframes, the availability of alternative collection points, and the minimisation of physical contact.At the same time, regulatory pressure regarding environmental responsibility is growing, particularly due to emission restrictions in central urban areas, the imperatives of sustainable transport provision, and the introduction of zero-emission zones, which are becoming the norm in leading countries.International experience points to an evolution towards radical innovative approaches, including autonomous unmanned aerial vehicles, automated postal terminals, micro-logistics storage facilities in residential areas, and artificial intelligence algorithms for the dynamic optimisation of transport routes.In the Ukrainian context, the relevance of this issue is heightened by the specific nature of the domestic market, which is witnessing rapid growth in online trade against a backdrop of infrastructure constraints, logistical challenges stemming from security concerns, and an urgent need for economic revitalisation in the post-war period.Domestic logistics operators have faced challenges such as a shortage of automated logistics hubs, staffing issues, and the need to develop flexible forms of cooperation.Research into innovative approaches in last-mile logistics is of fundamental importance for the development of sustainable development strategies.It creates the conditions not only for adopting proven global practices, but also for adapting them to local realities by forming hybrid models that integrate cutting-edge technological trends (the Internet of Things, blockchain technology, artificial intelligence) with national priorities for environmental modernisation.", "keywords": [ "Process (computing)", "Identification (biology)", "Product (mathematics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://nayka.com.ua/index.php/ee/article/download/10600/10744" }, { "id": "https://openalex.org/W7208807647", "doi": "10.5281/zenodo.22297603", "title": "When truck-paired drones save time and energy: capability interactions and a power-ratio boundary in last-mile delivery (solver + experiments)", "year": 2026, "publication_date": "2026-09-04", "type": "software", "language": "en", "authors": [ "Yifu Zhao", "Xiaofan Zou", "Junhao Wei", "Yanxiao Li", "Haochen Li", "Baili Lu", "Sio‐Kei Im", "Yapeng Wang", "Xu Yang" ], "first_author": "Yifu Zhao", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Reproducibility release for the Scientific Reports manuscript “When truck-paired drones save time and energy: capability interactions and a power-ratio boundary in last-mile delivery.” The archive contains the truck–drone routing solver, exact and diagnostic validation code, experiment and analysis drivers, pinned Python and Julia environments, cached road-network inputs, all retained seed-level results and routes, checkpoints, revision figures, protocol and deviation records, a release manifest, and per-file SHA-256 checksums. It supports the reported capability-interaction, operational-sensitivity, time–energy boundary, fixed-density, comparator, and road-geometry analyses. Larger-instance solutions are heuristic estimates and carry no optimality or near-optimality claim.", "keywords": [ "Drone", "Boundary (topology)", "Python (programming language)", "Heuristic", "Protocol (science)", "Reproducibility" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.22297603" }, { "id": "https://openalex.org/W4380874048", "doi": "10.1201/9781003415466-12", "title": "Novel scheduling heuristics for a truck-and-drone parcel delivery problem", "year": 2023, "publication_date": "2023-06-16", "type": "book-chapter", "language": "en", "authors": [ "Amrata Gill", "Prem Prakash Vuppuluri" ], "first_author": "Amrata Gill", "venue": null, "publisher": null, "abstract": "The combined use of trucks and drones for efficient package delivery has grown rapidly in recent years and finds applications in domains as varied as electronic commerce, providing timely humanitarian aid in calamity-impacted zones, and remote drug delivery. In such scenarios, a drone is frequently mounted on a delivery truck and used for delivering packages to a subset of the service points, typically those that are difficult to access by road but relatively close enough for the drone to quickly deliver and return to the truck. The drone plays a vital role in reducing delivery time along congested routes, ensuring timely supply of medication in hilly and rural areas and last-mile deliveries of critical resources in remote, poorly connected regions. A planning problem that arises in this context is that of finding a delivery route that minimizes some parameter, such as the total distance traveled by the truck and drone, while ensuring that all the packages are delivered, some by the drone and the others by truck. Several versions of this problem have been modeled as graph problems and extensively studied. This chapter presents a variant of the problem that considers delivery points that tend to form small, geographically close clusters. While a small number of delivery points in each cluster could be served by the truck, the remainder are better served by the drone. Formally, given a source warehouse and a set of destination sites, the objective is to construct a tour that enables the delivery truck to start from and return to the source warehouse, while traversing a subset of the delivery points earmarked for delivery by truck. Delivery points covered by the drone would be covered as and when the truck stops to make a delivery at a destination on its tour. The goal is to minimize the total distance required for the tour. Three constructive TSP heuristics are adapted for the truck-and-drone parcel delivery problem and their performance is studied on several test instances developed specifically for the problem.", "keywords": [ "Heuristics", "Truck", "Drone", "Scheduling (production processes)", "Computer science", "Operations research", "Operations management", "Engineering", "Operating system", "Aerospace engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1201/9781003415466-12" }, { "id": "https://openalex.org/W4200358140", "doi": "10.32907/ro-127-1965754101", "title": "Optimisation of truck-drone parcel delivery using GRASP", "year": 2021, "publication_date": "2021-12-06", "type": "article", "language": "en", "authors": [], "first_author": null, "venue": "Research outreach", "publisher": null, "abstract": null, "keywords": [ "Drone", "GRASP", "Truck", "Computer science", "Transport engineering", "Engineering", "Automotive engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://researchoutreach.org/wp-content/uploads/2021/12/Sarab-AlMuhaideb.pdf" }, { "id": "https://openalex.org/W7164809002", "doi": "10.1080/21681015.2026.2687521", "title": "A Joint economic lot size model for tuna supply chains with battery-constrained electric vehicles and drone-based last-mile delivery", "year": 2026, "publication_date": "2026-06-14", "type": "article", "language": "en", "authors": [ "Muhammad Ridwan Andi Purnomo", "Novrianty Rizky", "Elisa Kusrini", "Agus Salim Mansur", "Ivan Darma Wangsa", "Wakhid Ahmad Jauhari" ], "first_author": "Muhammad Ridwan Andi Purnomo", "venue": "Journal of Industrial and Production Engineering", "publisher": "Taylor & Francis", "abstract": "This study proposes a sustainable joint economic lot size (JELS) model for tuna supply chains under stochastic demand. The model considers a multi-echelon network consisting of a processor, a distribution center, multiple retailers, and end customers. Its novelty lies in integrating battery-constrained electric vehicles and drone-based delivery with stochastic demand and variable lead time, aspects rarely addressed simultaneously in previous studies. Lead time is formulated as a function of production, transportation, loading and unloading, transit, charging, and courier delivery activities. To solve the proposed model, an algorithm is developed and validated through a real-world case study. The results show that electric motorcycles achieve annual cost savings of IDR 8.469 billion (80.61%) compared to drones. Conversely, drones reduce delivery time by 2.32 days (55.42%) but increase carbon emissions by 3.13 t.CO₂e (2.65%). Sensitivity analysis identifies product weight, vehicle load capacity, speed, and transport distance as key factors affecting system performance.", "keywords": [ "Supply chain", "Tuna", "Key (lock)", "Electric vehicle", "Sensitivity (control systems)", "Joint (building)", "Variable (mathematics)", "Product (mathematics)", "Lead time", "Supply and demand" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/21681015.2026.2687521" }, { "id": "https://openalex.org/W7172244450", "doi": "10.21256/zhaw-37220", "title": "Launching drones from a vessel : routing unmanned aerial vehicles from a linearly moving depot", "year": 2026, "publication_date": "2026-07-30", "type": "article", "language": "en", "authors": [ "Nils Boysen", "Helmut Sedding" ], "first_author": "Nils Boysen", "venue": "Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)", "publisher": "ZHAW Zurich University of Applied Sciences", "abstract": null, "keywords": [ "Drone", "Depot", "Routing (electronic design automation)", "Cruise missile", "Mobile robot" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/11475/37220" }, { "id": "https://openalex.org/W2981408797", "doi": "10.2514/1.c035473", "title": "A Multi-Trip Vehicle Routing Problem for Small Unmanned Aircraft Systems-Based Urban Delivery", "year": 2019, "publication_date": "2019-10-21", "type": "article", "language": "en", "authors": [ "Younghoon Choi", "Bradford E. Robertson", "Youngjun Choi", "Dimitri N. Mavris" ], "first_author": "Younghoon Choi", "venue": "Journal of Aircraft", "publisher": "American Institute of Aeronautics and Astronautics", "abstract": "With the emergence of new technologies for small unmanned aircraft systems (sUAS), such as lightweight sensors and high-efficiency batteries, the operation of small unmanned aerial vehicles (sUAVs) will expand from military use to commercial use. A promising commercial application of sUAS is package delivery because of its potential to reduce acquisition and operating costs of the last-mile delivery system, while enabling new services such as same-day delivery. Moreover, in urban areas, sUAVs can deliver packages to customers without negatively affecting street traffic. To conduct urban operations, sUAS-based delivery systems must obey regulations for sUAS operations and avoid urban obstacles. In this paper, a maximum-flight-time-constrained multitrip vehicle routing problem with time windows optimization model is used to create routes for sUAS-based delivery missions. To address the actual urban environment with the optimization model, a two-layered urban flight network is built by feeding an airborne light detection and ranging sensor data into an algorithm that uses a Voronoi diagram to create collision-free paths. This paper uses this approach to study a possible package delivery using sUAS in San Diego, CA.", "keywords": [ "Routing (electronic design automation)", "Computer science", "Vehicle routing problem", "Transport engineering", "Real-time computing", "Engineering", "Computer network" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2514/1.c035473" }, { "id": "https://openalex.org/W7171775806", "doi": "10.1007/s10951-026-00879-y", "title": "Launching drones from a vessel: routing unmanned aerial vehicles from a linearly moving depot", "year": 2026, "publication_date": "2026-07-30", "type": "article", "language": "en", "authors": [ "Nils Boysen", "Helmut Sedding" ], "first_author": "Nils Boysen", "venue": "Journal of Scheduling", "publisher": "Springer Science+Business Media", "abstract": "Abstract Unmanned aerial vehicles (or drones) are expected to free urban areas from the negative impacts of traditional last-mile delivery by trucks and vans. To overcome one of the major operational challenges of drones, their limited range, existing concepts propose to launch them either from decentralized depots or trucks moving through the city center. Both solutions have drawbacks, so recent ideas suggest using river barges as mobile launch platforms. These ships act as linearly moving depots for drone launches, and this paper investigates the resulting routing problem when serving a given set of customers. First, we formulate the basic optimization problem and derive some structural properties through an in-depth computational complexity analysis. Based on these insights, we derive appropriate methods to attain exact, $$\\rho $$ ρ -approximative, or heuristic solutions, and apply them to evaluate the potential savings of delivery vans (benchmarked as a standalone delivery option and as a van-drone tandem) if, instead, drones are launched from ships or trains.", "keywords": [ "Drone", "Truck", "Routing (electronic design automation)", "Heuristic", "Vehicle routing problem", "Set (abstract data type)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10951-026-00879-y" }, { "id": "https://openalex.org/W7167073031", "doi": "10.3390/su18136728", "title": "Beyond the Last Mile: A Systematic Review Exploring Indoor Delivery-UAV Requirements in the Last-Meter Context", "year": 2026, "publication_date": "2026-07-02", "type": "review", "language": "en", "authors": [ "Y Li", "S Thomas Ng", "Mingzhuo Ling", "Qi Pan" ], "first_author": "Y Li", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The final stage of urban logistics does not end at the building entrance but continues within complex, vertically structured indoor environments, where conventional ground-based delivery systems face limitations in efficiency, flexibility, and scalability. This study introduces the concept of last-meter delivery, defined as unmanned aerial vehicle (UAV)-enabled transport from the building envelope to the recipient within global navigation satellite system (GNSS)-denied, building-regulated indoor space, and systematically reviews the literature from two traditionally separate domains: indoor-UAV operation in GNSS-denied spaces, and outdoor-UAV-based logistics. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 297 studies are synthesized through a two-stream thematic synthesis. The review makes three contributions. First, a unified analytical framework is developed across four dimensions (spatial mobility, logistical capability, social acceptance, and operational coordination) through which the two bodies of literature are shown to be largely complementary, with the gaps in one stream coinciding with the strengths of the other. Second, indoor aerial delivery is found to be subject to a distinct set of operational constraints, including micro-scale navigation accuracy, strict geometric safety envelopes, close human–UAV interaction, and privacy sensitivity, implying that indoor transport-UAVs cannot be realized through simple miniaturization of outdoor platforms but require precision-oriented, human-centric, and building-aware design. Third, the four dimensions are translated into a building-management-oriented indicator framework covering spatial compliance, handover standardization, building information modeling (BIM) integration, occupant consent, and liability allocation, reframing last-meter requirements in terms that are actionable for building planners and facility managers. By framing these challenges within the last-meter perspective, this review identifies the gap between current last-mile theories and emerging in-building aerial logistics and provides a structured foundation for future research.", "keywords": [ "Framing (construction)", "USable", "Context (archaeology)", "Cognitive reframing", "Architecture", "Usability", "Set (abstract data type)", "Rendering (computer graphics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/18/13/6728/pdf?version=1782995255" }, { "id": "https://openalex.org/W3118930962", "doi": null, "title": "Acceptance of drone delivery is limited (not only) by noise concerns", "year": 2020, "publication_date": "2020-10-20", "type": "conference-paper", "language": "en", "authors": [ "Hinnerk Eißfeldt" ], "first_author": "Hinnerk Eißfeldt", "venue": "elib (German Aerospace Center)", "publisher": "Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)", "abstract": "In recent years, civil drones have become increasingly present in the media and in everyday life. There has been a high level of interest in drone delivery from the very beginning, yet public acceptance of drone delivery still seems limited, with acceptance rates usually ranging from 30 to 40%. The present paper reports findings of a representative national study about the acceptance of civilian drones in Germany. Several factors limiting the support of drone delivery such as concerns about traffic safety, noise, and animal welfare are identified. In addition, effects of drone experience are discussed, showing all areas of concern being reported at higher rates by participants who had no experience with civil drones. For noise concerns however, among those reporting having experience with drones, a more detailed look into the kind of experience with drones revealed a significantly higher percentage of noise concern among those reporting having heard a drone compared to those who reported that they had not. Moreover, an effect of NIMBYism is confirmed in the context of drone delivery, as even among residents envisioning own usage of drones for parcel delivery, the overflight of the own home is frequently not agreed with. This particular effect is termed NOMOH (Not Over My Own Home). Finally, the need for regulation is discussed as well as potential measures to increase acceptance of drone delivery. Besides defining certain urban areas and time restrictions, installing means of noise control or providing tools for participatory noise sensing to residents can also be viable measures to increase public support. If the acceptance level among residents remains in the range of below one third, drone delivery will not become a successful service in western cities.", "keywords": [ "Drone", "Context (archaeology)", "Business", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://elib.dlr.de/136906/1/Ei%C3%9Ffeldt%202020%20Acceptance%20of%20drone%20delivery%20is%20limited%20%28not%20only%29%20by%20noise%20concerns.pdf" }, { "id": "https://openalex.org/W7112586127", "doi": null, "title": "Consumer preferences and barriers in the adoption of drone delivery services", "year": 2025, "publication_date": "2025-11-27", "type": "article", "language": "en", "authors": [ "Dabić, Marina", "Ferreira, João J. M.", "Marques Lopes, João", "Gomes, Sofia" ], "first_author": "Dabić, Marina", "venue": "Repository of the University of Ljubljana (University of Ljubljana)", "publisher": "University of Ljubljana", "abstract": "Drone parcel delivery is an emerging topic with drone suppliers and retailers concerned due to their challenges and implications. Despite the many advantages associated with the drone delivery service, there are still obstacles to its acceptance by consumers, which is why it is necessary to understand their motivations. This study aims to analyze consumer behavior in the adoption of drone services. Specifically, the study analyzes the influence of perceived ease of use, perceived usefulness, and perceived privacy risk on consumers' attitudes toward drone delivery services and their intention to adopt this service. The sample, collected through a questionnaire, comprises answers from 1,108 Portuguese citizens. The Partial Least Squares method was used to test the purpose of this study. The results suggest that consumers' willingness to adopt drone delivery services is positively affected by the perception of ease of use and usefulness. At the same time, it is negatively influenced by perceived privacy risk. In addition, consumers' attitudes significantly influence consumers' intention to use these services in the future. Geographic adoption of drone delivery services is still limited. This study allows us to deepen our knowledge about the potential consumers of this service, which is very useful for its more universal adoption, and we propose to test the extended TAM model for ease of use of drone technologies by Portuguese consumers.", "keywords": [ "Drone", "Usability", "Risk perception", "Perception", "Test (biology)", "Technology acceptance model" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://repozitorij.uni-lj.si/IzpisGradiva.php?id=176311" }, { "id": "https://openalex.org/W7113758794", "doi": null, "title": "Digital and technical solutions within last mile deliveries : A study of how delivery companies can meet consumers' demands for last-mile deliveries", "year": 2020, "publication_date": "2020-01-01", "type": "dissertation", "language": "sv", "authors": [ "Sörbom, Josefine", "Bjurlemark, Adelaide" ], "first_author": "Sörbom, Josefine", "venue": "Diva portal (Dalarna University Library)", "publisher": null, "abstract": "E-commerce is in a growing phase where consumers are getting more aware, picky and comfortable when it comes to delivery of their packages. This case study investigates the requirements that consumers have regarding last-mile deliveries as well as various digital logistic solutions that may meet these requirements. In the study, relevant people in three different companies working with delivery, have been selected to get a deeper insight into how companies view consumers' new requirements and how they work to meet these and how they reflect about the future when it comes to last-mile deliveries. Consumers now expect a faster and more flexible service where they can design the last-mile delivery according to their premises, e.g. time, location, etc. The demands emerging associated with the expansion of e-commerce include faster, cheaper and more flexible deliveries. Transparency in environmental issues and work processes has also become an important factor for many consumers today, which may be decisive for purchasing power. Collaboration with other actors enables e-commerce companies to streamline their delivery alternatives in the form of outsourcing. This approach can be done through collaboration with other logistics players or in the form of crowdsourcing. The term E-logistics implies a system that contains various parts of a logistic process in which the exchange takes place with both the help of technology and the internet. In combination with a functioning digital infrastructure and e-logistics, delivery processes can become more effective. New technologies such as parcel locks, drones and delivery robots are being analyzed as potential solutions to streamline last-mile deliveries.", "keywords": [ "Work (physics)", "Last mile (transportation)", "Process (computing)", "Transparency (behavior)", "Purchasing", "Emerging technologies", "Service (business)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-44607" }, { "id": "https://openalex.org/W7197185318", "doi": null, "title": "Development Of An Integrated Navigation System For Urban Drone Delivery", "year": 2023, "publication_date": "2023-11-24", "type": "article", "language": "en", "authors": [ "Mohamed Alaaeldin Hassan Ahmed Aly" ], "first_author": "Mohamed Alaaeldin Hassan Ahmed Aly", "venue": "University of Debrecen Electronic Archive (University of Debrecen)", "publisher": "University of Debrecen", "abstract": "The thesis, titled \"Development of an Integrated Navigation System for Urban Drone Delivery,\" explores the creation of an autonomous drone delivery system tailored for urban settings. It addresses the shortcomings of traditional delivery methods and advocates for the use of drones in urban delivery. The proposed solution centers around an integrated navigation system in the Simulation In The Loop employing technologies such as the drone autopilot, simulation software, ground control station (GCS), and the robot operating system (ROS) framework. The experimental setup encompasses various components, including Ubuntu installation, catkin workspace, python virtual environment, PX4 firmware configuration, Gazebo simulation, QGroundControl setup, and ROS integration. The experimental results highlight the system's efficacy in areas like connection and communication status, manual control, autonomous takeoff and landing missions, path planning, and autonomous mission following. Then, the thesis concludes by discussing these findings and speculating on the potential impact of the autonomous drone delivery system on urban logistics.", "keywords": [ "Drone", "Firmware", "Python (programming language)", "Navigation system", "Robot", "Control system", "Motion planning", "Urban environment" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/2437/365900" }, { "id": "https://openalex.org/W3179120948", "doi": "10.35685/revintera.v5i2.898", "title": "New Horizons For Last Mile Delivery After The Coronavirus Novel", "year": 2021, "publication_date": "2021-07-02", "type": "article", "language": "en", "authors": [ "Paulo Rossi Croce", "João José de Assis Rangel", "Geísa Pereira Marcilio Nogueira" ], "first_author": "Paulo Rossi Croce", "venue": "Revista Interação Interdisciplinar.", "publisher": null, "abstract": "The COVID-19 outbreak infected millions of people around the globe, forcing the people stay home. The new daily life became indoor shopping and the retailers had to adapt to this new reality, causing a high demand for the logistics. This paper presents the willingness of a post-pandemic medium-sized city consumers to adopt new modalities of delivery: reception boxes, delivery drones and crowdsourcing logistics. Through a survey with closed questions applied online to 401 people, the results indicated that younger people tend to buy more online than older ones. People with a higher education level also buys more online. It was possible to affirm that the popular opinion was positive towards experimenting these innovations and the presented results corroborates with the related research.", "keywords": [ "Mile", "Coronavirus disease 2019 (COVID-19)", "Coronavirus", "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)", "2019-20 coronavirus outbreak", "New horizons", "Virology", "Computer science", "Medicine", "Geography", "Engineering", "Geodesy" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.35685/revintera.v5i2.898" }, { "id": "https://openalex.org/W4320927589", "doi": "10.48550/arxiv.2103.04015", "title": "Dynamic Resource Management for Providing QoS in Drone Delivery Systems", "year": 2021, "publication_date": "2021-03-06", "type": "preprint", "language": "en", "authors": [ "Behzad Khamidehi", "Majid Raeis", "Elvino Silveira Sousa" ], "first_author": "Behzad Khamidehi", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "Drones have been considered as an alternative means of package delivery to reduce the delivery cost and time. Due to the battery limitations, the drones are best suited for last-mile delivery, i.e., the delivery from the package distribution centers (PDCs) to the customers. Since a typical delivery system consists of multiple PDCs, each having random and time-varying demands, the dynamic drone-to-PDC allocation would be of great importance in meeting the demand in an efficient manner. In this paper, we study the dynamic UAV assignment problem for a drone delivery system with the goal of providing measurable Quality of Service (QoS) guarantees. We adopt a queueing theoretic approach to model the customer-service nature of the problem. Furthermore, we take a deep reinforcement learning approach to obtain a dynamic policy for the re-allocation of the UAVs. This policy guarantees a probabilistic upper-bound on the queue length of the packages waiting in each PDC, which is beneficial from both the service provider's and the customers' viewpoints. We evaluate the performance of our proposed algorithm by considering three broad arrival classes, including Bernoulli, Time-Varying Bernoulli, and Markov-Modulated Bernoulli arrivals. Our results show that the proposed method outperforms the baselines, particularly in scenarios with Time-Varying and Markov-Modulated Bernoulli arrivals, which are more representative of real-world demand patterns. Moreover, our algorithm satisfies the QoS constraints in all the studied scenarios while minimizing the average number of UAVs in use.", "keywords": [ "Computer science", "Drone", "Bernoulli's principle", "Quality of service", "Markov decision process", "Queueing theory", "Queue", "Resource allocation", "Mathematical optimization", "Real-time computing", "Delivery Performance", "Distributed computing" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2103.04015" }, { "id": "https://openalex.org/W3105098569", "doi": null, "title": "Uav last-mile delivery in the humanitarian aid context - a qualitative analysis of the implementations in the health supply chain", "year": 2020, "publication_date": "2020-01-21", "type": "dissertation", "language": "en", "authors": [ "Kristina Ruth Babette Weber" ], "first_author": "Kristina Ruth Babette Weber", "venue": "New University of Lisbon's Repository (New University of Lisbon)", "publisher": null, "abstract": "Drones as innovative transportation mode for medical supplies have the potential to contribute significantlyto humanitarian aid. Building on three key case studies and fivein-depthinterviews, this work projectdeveloped a conceptual frameworkillustrating the success drivers and factors of UAV delivery in the health supply chain. Thefour identified main categories of the project environment, namely project operators, UAV environment, regulatory environment and public,are influenced by local conditions and specifications of thecargo. Thefocus on and understanding of all interdependent dimensionsis crucial for a project’s success. However, to allow for scalable operations,technological featuresandregulatory environments require further development.", "keywords": [ "Implementation", "Last mile (transportation)", "Supply chain", "Context (archaeology)", "Mile", "Qualitative research", "Qualitative analysis", "Operations management", "Engineering", "Business", "Computer science", "Process management" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/10362/107188" }, { "id": "https://openalex.org/W7204225114", "doi": "10.2139/ssrn.7353598", "title": "Cooperative Control of Heterogeneous UAV-UGV Systems for Low-Altitude Last-Mile Delivery with Mobile Ground Support", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Weihan Xu", "Xuehang Bian", "Tianqi Wang" ], "first_author": "Weihan Xu", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Trajectory", "Task (project management)", "Energy consumption", "Controller (irrigation)", "Model predictive control", "Control (management)", "Energy (signal processing)", "Vehicle dynamics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.7353598" }, { "id": "https://openalex.org/W7167841031", "doi": "10.13140/rg.2.2.14361.17760", "title": "Transforming Last-Mile Healthcare Logistics through an Accessible Mobile–UAV Ecosystem for Medication Delivery", "year": 2026, "publication_date": "2026-07-09", "type": "article", "language": "en", "authors": [ "Patricia Acosta-Vargas", "Luis Salvador-Ullauri", "Gloria Acosta-Vargas", "Hugo Arias-Flores", "Luis Fernando Aguas Bucheli" ], "first_author": "Patricia Acosta-Vargas", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Health care", "Ecosystem", "Healthcare delivery", "Healthcare system", "Supply chain", "Work (physics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.13140/rg.2.2.14361.17760" }, { "id": "https://openalex.org/W7204343346", "doi": null, "title": "Governing the skies: Priorities and policy pathways for the future of drone deliveries", "year": 2025, "publication_date": "2025-07-22", "type": "report", "language": "en", "authors": [ "Daniela Paddeu", "Eda Beyazıt" ], "first_author": "Daniela Paddeu", "venue": "UWE Research Repository (UWE Bristol)", "publisher": "University of the West of England", "abstract": "This policy briefing explores the governance challenges and policy priorities for integrating drone-based last-mile deliveries into the UK transport system. Despite growing interest and investment, widespread adoption remains hindered by fragmented regulation, limited planning guidance, and public mistrust. Drawing on stakeholder engagement and foresight methods, the research highlights five critical domains—planning, regulation, public engagement, industry collaboration, and central-local government alignment—as key to shaping a safe, equitable, and sustainable drone delivery ecosystem. The briefing calls for proactive governance frameworks that embed environmental safeguards, enable innovation, and prioritise public benefit to ensure drones contribute positively to the future of mobility.", "keywords": [ "Drone", "Futures studies", "Government (linguistics)", "Corporate governance", "Stakeholder engagement", "Stakeholder", "Public policy", "Key (lock)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://uwe-repository.worktribe.com/preview/14699157/Policy%20Doc%20-%20Governing%20the%20skys%20%20-%20final%2022%20Jul%202025.pdf" }, { "id": "https://openalex.org/W7165647828", "doi": "10.3390/drones10070477", "title": "Reinforcement-Learning-Based Hybrid Truck–Drone Delivery Optimization", "year": 2026, "publication_date": "2026-06-23", "type": "article", "language": "en", "authors": [ "Youyao Gao", "Tongchang Liu", "Huan Jin" ], "first_author": "Youyao Gao", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "This paper studies large-scale last-mile delivery using a heterogeneous fleet of trucks, onboard drones in a hybrid truck–drone mode, and independent drones. Orders are first screened by a feasibility check; feasible orders are then assigned to one of the three modes by a delivery mode selection policy and routed using mode-specific planning algorithms. The delivery mode selection policy is trained with Proximal Policy Optimization (PPO), warm-started by behaviour cloning from heuristic decisions. For route planning, we use a five-step procedure for the hybrid mode and simple depot round trips for independent drones. Experiments on Solomon VRPTW benchmarks and extended instances (100/200/400 customers; R/C/RC distributions) show lower total cost than representative heuristic baselines and metaheuristics, with practical runtime. Sensitivity analysis over fleet sizes further indicates competitive performance across a range of truck and drone configurations, especially for medium and large fleets.", "keywords": [ "Heuristic", "Truck", "Selection (genetic algorithm)", "Mode (computer interface)", "Range (aeronautics)", "Drone", "Sensitivity (control systems)", "TRIPS architecture" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3390/drones10070477" }, { "id": "https://openalex.org/W2727900798", "doi": "10.13140/rg.2.2.24807.96163", "title": "A Comparison of Brick-and-Mortar and Online Last Mile Delivery Networks", "year": 2017, "publication_date": "2017-01-01", "type": "article", "language": "en", "authors": [ "Dennis Corvi" ], "first_author": "Dennis Corvi", "venue": "Journal of international women's studies", "publisher": "Bridgewater State University", "abstract": "Driven by the rapid growth of e-commerce, last mile delivery has become an increasingly necessary strategy for retailers to stay competitive. The locations of distribution centers and the capacity of vehicles have profound effects on transportation costs. Demand for same-day delivery services is expected to increase in popularity as new technologies, such as drones and automated transportation, evolve and become cheaper to develop. Organizations that design their logistic network efficiently hold the largest competitive advantage. Amazon is currently an industry leader in shipping and delivery logistics by utilizing its online ordering process. Brick-and-mortar stores such as Walmart and Best Buy are trying to keep pace by similarly offering online ordering and curbside delivery using outsourced delivery services. When considering the most effective method of delivery, one consideration is whether a delivery system can balance its ability to drive down the distance driven by its fleet while increasing the density of packages that are to be delivered. In this regard, modeling and simulation software can be used effectively to run sensitivity analysis to understand key performance indicators of transportation costs, enabling organizations to estimate the most effective ways to deliver products to consumers. Additionally, simulation can be used to make larger organizational decisions relating to the supply chain. In this thesis, logistic simulation modeling software, anyLogistix, is combined with Geographic Information System (GIS) technology to investigate the most cost efficient mode of delivery network. The results of this study demonstrate that a network with fewer distribution centers will have higher transportation costs due to a greater distance to cover.", "keywords": [ "Mile", "Last mile (transportation)", "Brick and mortar", "Mortar", "Brick", "Engineering", "Architectural engineering", "Telecommunications", "Computer science", "Civil engineering", "Geography", "World Wide Web" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://vc.bridgew.edu/honors_proj/203" }, { "id": "https://openalex.org/W4395468537", "doi": "10.56642/brdu.v03i04.012", "title": "Design a last mile delivery (Model for e-commerce firm)", "year": 2024, "publication_date": "2024-04-01", "type": "article", "language": "ca", "authors": [ "Yash Mishra", "Gaurav Gupta" ], "first_author": "Yash Mishra", "venue": "Poonam Shodh Rachna", "publisher": null, "abstract": "In the era of e-commerce becoming a pervasive integral part in different retail business sectors, lastmile delivery is now a major problem across urban areas globally.Supply chain customers are increasingly demanding their orders to be sent home.The increase in truck traffic causing traffic jams, emissions, and health problems associated with the incessant presence of delivery vehicles in city centers is a matter of growing concern.As a result, interesting new conceptions of the last mile delivery come as no wonder and arise in last thirty years.Unmanned aerial vehicles (drones) and autonomous pods for parcels are the most prominent inventions of robots directed to the kindest modification of parcel deliveries.This paper offers an extensive review of for-public last-mile delivery types and operations in terms of decision making.The review will pay a special attention to the process of establishing and operating last mile delivery types.Achieving this goal will require us to systematically present the various delivery concepts, organize them using a concise notation scheme, and discuss problems pertaining to the decision-making process while considering existing research findings relating to operations research methods that were used toward the solving of these problems.Additionally, we also consider possible layouts for upcoming research, focusing on the directions for future investigation in this particular area.", "keywords": [ "Mile", "Last mile (transportation)", "Business", "Computer science", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.56642/brdu.v03i04.012" }, { "id": "https://openalex.org/W4403851677", "doi": "10.54254/2754-1169/121/20242550", "title": "Optimization and Application Analysis of the UAV \"Last Mile\" Mobile Terminal Distribution Station in Rural Area under the Background of E-Commerce", "year": 2024, "publication_date": "2024-10-25", "type": "article", "language": "en", "authors": [ "Zhongsheng Luo" ], "first_author": "Zhongsheng Luo", "venue": "Advances in Economics Management and Political Sciences", "publisher": null, "abstract": "With the booming demands of global consumers, the grand total of international e-commercial procurement in 2024 will be expected to exceed 6.3 trillion USD. Under the pressure of huge orders and shipping lag, figuring out a cost-effective last mile delivery achieving real door-to-door service, especially in rural areas, has become one of the focuses in the international e-commercial market. To better solve this problem, this paper starts with the analysis of international e-commercial status and the feasibility of UAV mobile terminal station launch, taking good account of drone delivery route setting, time schedule, and costs spent to optimize the mobile station moving. Based on a series of experiments to iterate the Unmanned Aerial Vehicle (UAV) mobile terminal station delivery mode, it will provide some insights to the market about how the last mile delivery will develop in the next decade. This paper will focus on applying the hybrid ant colony algorithm to improve truck-drone collaborative last mile delivery route settings and figure out the best delivery route combo for cost saving.", "keywords": [ "Terminal (telecommunication)", "Mile", "Last mile (transportation)", "Computer science", "Transport engineering", "Telecommunications", "Geography", "Engineering", "Geodesy" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://aemps.ewapub.com/article/view/16299.pdf" }, { "id": "https://openalex.org/W7211904879", "doi": "10.1016/j.techfore.2026.124875", "title": "Total interpretive structural modeling of UAV adoption in middle- and last-mile logistics: A sociotechnical systems perspective", "year": 2026, "publication_date": "2026-09-07", "type": "article", "language": "en", "authors": [ "Francesca Mancini Barbieri", "Claudia Colicchia", "Eric H. Grosse", "Marco Lovera", "Alessandro Creazza" ], "first_author": "Francesca Mancini Barbieri", "venue": "Technological Forecasting and Social Change", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Sociotechnical system", "Perspective (graphical)", "Key (lock)", "System dynamics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.techfore.2026.124875" }, { "id": "https://openalex.org/W7168250182", "doi": "10.1109/ctus-emea68989.2025.11592324", "title": "Enhancing Sustainable Last-Mile Delivery through AI: Innovations in Route Optimisation, Dynamic Pricing Strategies, and Seamless Integration of Autonomous Vehicles and Drones", "year": 2025, "publication_date": "2025-11-27", "type": "conference-paper", "language": null, "authors": [ "Tekena Akraka", "Olayiwola Zadiq Gidado", "Adela Istifanus", "Ezekiel Odiaka" ], "first_author": "Tekena Akraka", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Drone", "Key (lock)", "Dynamic pricing", "Process (computing)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/ctus-emea68989.2025.11592324" }, { "id": "https://openalex.org/W3216465182", "doi": "10.9734/bpi/ramrcs/v5/1641a", "title": "A Study on Optimization of Truck-Drone Parcel Delivery Using Metaheuristics", "year": 2021, "publication_date": "2021-11-22", "type": "book-chapter", "language": "en", "authors": [ "Sarab AlMuhaideb", "Taghreed Alhussan", "Sara Alamri", "Yara Altwaijry", "Lujain Aljarbou", "Haifa Alrayes" ], "first_author": "Sarab AlMuhaideb", "venue": "Book Publisher International (a part of SCIENCEDOMAIN International)", "publisher": null, "abstract": "This research addresses a variant of the traveling salesman problem in drone-based delivery systems known as the TSP-D. The TSP-D is a combinatorial optimization problem in which a truck and a drone collaborate to deliver parcels to customers, with the objective of minimizing the total delivery time. Determining the optimal solution is NP-hard; thus, the size of the problems that can be solved optimally is limited. Therefore, metaheuristics are used to solve the problem. Metaheuristics are adaptive and intelligent algorithms that have proved their success in many similar problems. This study proposes a hybrid meta-heuristic solution to the TSP-D problem, where the solution is initialized from the optimal TSP solution reached by the Concorde TSP solver. Next, the delivery routes for the truck and the drone are obtained using the greedy, randomized adaptive search procedure (GRASP) with two local search alternatives. The main contribution of this work is the application of self-adaptive selection when searching the neighbourhood in GRASP. The proposed approach was tested on 200 instances with different properties from the publicly available ”Instances of TSP with Drone” benchmark. Results were evaluated against state-of-the-art algorithms. Nonparametric statistical tests concluded that the proposed approach has comparable performance to the rival algorithms (p = 0:074) in terms of tour duration. The proposed approach has better or similar performance in instances where the drone and truck have the same speed (\\(\\alpha\\) = 1).", "keywords": [ "Metaheuristic", "Drone", "Travelling salesman problem", "GRASP", "Mathematical optimization", "Solver", "Computer science", "Truck", "Benchmark (surveying)", "Heuristic", "Local search (optimization)", "Greedy randomized adaptive search procedure" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.9734/bpi/ramrcs/v5/1641a" }, { "id": "https://openalex.org/W7117969768", "doi": "10.1007/978-3-032-10126-6_18", "title": "Relevance and Future State of Research on Advanced Systems in Last Mile Logistics", "year": 2025, "publication_date": "2025-01-01", "type": "conference-paper", "language": "en", "authors": [ "José Ramón Salcedo Hernández", "Jesús Muñuzuri" ], "first_author": "José Ramón Salcedo Hernández", "venue": "Lecture notes on data engineering and communications technologies", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Maturity (psychological)", "Leverage (statistics)", "Last mile (transportation)", "Relevance (law)", "Emerging technologies", "Capability Maturity Model", "Work (physics)", "Humanitarian Logistics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-032-10126-6_18" }, { "id": "https://openalex.org/W4312535465", "doi": "10.2139/ssrn.4234590", "title": "A Variable Neighborhood Search for Parcel Delivery by Vehicle with Drone Cycle", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Amro M. El-Adle", "Ahmed A. Ghoniem", "Mohamed Haouari" ], "first_author": "Amro M. El-Adle", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Computer science", "Benchmark (surveying)", "Heuristic", "Travelling salesman problem", "Rendezvous", "Operations research", "Key (lock)", "Engineering", "Artificial intelligence", "Geography", "Aerospace engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4234590" }, { "id": "https://openalex.org/W7118182378", "doi": "10.1109/miot.2025.3644407", "title": "Multi-Sized AI Models Assisted Low-Altitude UAV Delivery With RAN Optimization", "year": 2026, "publication_date": "2026-01-05", "type": "article", "language": null, "authors": [ "Longyu Zhou", "Supeng Leng", "Zonghang Li", "Tianhao Liang", "Tony Q. S. Quek" ], "first_author": "Longyu Zhou", "venue": "IEEE Internet of Things Magazine", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "With the development of Artificial Intelligence (AI) 1technology and wireless communication technology, Uncrewed Aerial Vehicles (UAVs)-based low-altitude applications have become increasingly attractive for accurate and real-time UAV delivery by performing cooperative path planning. However, this application exposes imperative computing requirements on resource-limited UAVs. To address the problem, we propose a multi-sized AI model-assisted parcel delivery framework with RAN resource optimization. In this design, we propose a double-scale AI model cooperation algorithm to implement highly accurate UAV path planning for safe parcel delivery. We then propose a transformer-based resource optimization algorithm to perform high-efficiency resource allocation for real-time and reliable communication and computing cooperation among UAVs. Simulation results demonstrate that our algorithm improves network throughput by 15.4% compared to other benchmarks on average while achieving a high successful delivery ratio of 92% for robust UAV delivery.", "keywords": [ "Resource allocation", "Throughput", "Path (computing)", "Resource management (computing)", "Wireless", "Resource (disambiguation)", "Wireless network" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/miot.2025.3644407" }, { "id": "https://openalex.org/W3012629598", "doi": "10.1145/3389400.3389407", "title": "Simulating Hybrid Aerial- and Ground-based Vehicular Networks with ns-3 and LIMoSim", "year": 2020, "publication_date": "2020-06-07", "type": "conference-paper", "language": "en", "authors": [ "Benjamin Sliwa", "Manuel Patchou", "Karsten Heimann", "Christian Wietfeld" ], "first_author": "Benjamin Sliwa", "venue": null, "publisher": null, "abstract": "Integrating Unmanned Aerial Vehicles (UAVs) into future Intelligent Transportation Systems (ITSs) allows to exploit their unique mobility potentials for improving the performance of services such as near-field parcel delivery, dynamic network provisioning, and aerial sensing. In order to provide a controllable environment for the methodological performance analysis, simulation frameworks need to support ground- and aerial-based mobility as well as the involved communication technologies. In this paper, we present the open source Lightweight ICT-centric Mobility Simulation (LIMoSim) framework for simulating hybrid vehicular networks within Network Simulator 3 (ns-3). LIMoSim implements a shared codebase coupling approach which integrates all required components in a single simulation process. The low-level mobility behaviors rely on well-known analytical models. Different case studies discussing cutting-edge communication technologies such as Cellular Vehicle-to-Everything (C-V2X) and millimeter Wave (mmWave) are presented in order to illustrate how the proposed framework can be integrated into ns-3-based network simulation setups.", "keywords": [ "Codebase", "Computer science", "Exploit", "Provisioning", "Process (computing)", "Enhanced Data Rates for GSM Evolution", "Field (mathematics)", "Intelligent transportation system", "Distributed computing", "Cellular network", "Network simulation", "Computer network" ], "cited_by_count": 15, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2003.09829" }, { "id": "https://openalex.org/W4408933840", "doi": "10.15294/rji.v3i1.4430", "title": "QR-Code Based Visual Servoing and Target Recognition to Improve Payload Release Accuracy in Air Delivery Missions using Fully Autonomous Quad-Copter UAV", "year": 2025, "publication_date": "2025-03-28", "type": "article", "language": "en", "authors": [ "Bondan Eka Nugraha", "Zaenal Abidin" ], "first_author": "Bondan Eka Nugraha", "venue": "Recursive Journal of Informatics", "publisher": null, "abstract": "Abstract. Unmanned Aerial Vehicles (UAVs) are increasingly utilized for package delivery due to their efficiency and automation capabilities. UAVs can execute autonomous flight missions using Global Positioning System (GPS)-based navigation. However, challenges arise in the final stage of delivery, known as the last-mile delivery problem. The limitations of GPS-based navigation, the absence of recipient authentication, and shifting drop-off points create reliability and safety concerns. External factors such as varied environmental topography further contribute to delivery inaccuracies, highlighting the need for a more precise approach. Purpose: Many studies have explored UAV navigation and delivery systems, but challenges in last-mile delivery remain unresolved. This research introduces an improved UAV delivery system using computer vision (CV) and image-based visual servoing (IBVS) with QR Codes as location markers. The aim is to enhance UAV navigation accuracy and recipient verification, ensuring more reliable package deliveries. Methods/Study design/approach: The study implements a CV-based navigation system where QR Codes serve as landing markers for UAVs. Image processing is conducted using a companion computer linked to the UAV's flight control system. The IBVS method enables UAVs to adjust their position in real-time, minimizing GPS errors. Recipient verification is performed through QR Code scanning before releasing the package. The system is tested through computer simulations and real flight experiments to assess accuracy and effectiveness. Result/Findings: Experimental results demonstrate that UAVs equipped with the IBVS method can successfully complete package delivery missions with improved accuracy. GPS errors are corrected by aligning the UAV's position with QR Code markers, and recipient authentication is verified before package release. Real-flight tests confirm that this approach significantly enhances UAV delivery reliability compared to conventional GPS-based navigation. Novelty/Originality/Value: This research presents a novel integration of computer vision and UAV navigation for addressing last-mile delivery challenges. By leveraging IBVS and QR Code-based authentication, UAVs can perform fully autonomous, precise, and secure package deliveries. This method offers a viable solution to improve UAV-based logistics, reducing delivery errors and enhancing operational safety.", "keywords": [ "Payload (computing)", "Visual servoing", "Computer vision", "Code (set theory)", "Artificial intelligence", "Computer science", "Real-time computing", "Image (mathematics)", "Computer network" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.15294/rji.v3i1.4430" }, { "id": "https://openalex.org/W4412693546", "doi": "10.5815/ijisa.2025.04.01", "title": "An Enhanced Adaptive B-spline Smoothing Approach for UAV Path Planning", "year": 2025, "publication_date": "2025-07-28", "type": "article", "language": "en", "authors": [ "Mykola Nikolaiev", "Mykhailo Novotarskyi" ], "first_author": "Mykola Nikolaiev", "venue": "International Journal of Intelligent Systems and Applications", "publisher": null, "abstract": "This paper presents an Enhanced Adaptive B-Spline Smoothing approach for UAV path planning in complex three-dimensional environments. By leveraging the inherent local control and smoothness properties of cubic B-Splines, the proposed method integrates an adaptive knot selection mechanism—optimized via a genetic algorithm—with curvature-aware control point refinement to generate dynamically feasible and smooth flight paths. Simulation studies in a cluttered 3D airspace show that the proposed technique reduces path length and lowers maximum curvature compared to uniform and chord-length-based B-Spline strategies. Despite a moderate computational overhead, the results demonstrate smoother, more stable flight trajectories that adhere to aerodynamic constraints and ensure safe obstacle avoidance. This approach is particularly valuable for near-real-time missions, where flight stability, rapid re-planning, and energy efficiency are paramount. Results emphasize the potential of the proposed method for improving UAV navigation in various applications—such as urban logistics, infrastructure inspection, and search-and-rescue—by providing better maneuverability, reduced energy consumption, and increased operational safety to the UAV agents.", "keywords": [ "Computer science", "Smoothing", "Motion planning", "Obstacle avoidance", "Smoothness", "Mathematical optimization", "Path (computing)", "Spline (mechanical)", "Curvature", "Energy consumption", "Control theory (sociology)", "Real-time computing" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5815/ijisa.2025.04.01" }, { "id": "https://openalex.org/W4412486277", "doi": "10.2514/6.2025-3686", "title": "Autonomous Flight of UAV in Complex Multi-Obstacle Environment Using Data-Driven and Vision-Based Deep Reinforcement Learning and AirSim", "year": 2025, "publication_date": "2025-07-16", "type": "conference-paper", "language": "en", "authors": [ "Taehyun Ko", "Jinhyuk Park", "Seongim Choi", "Junki Shim" ], "first_author": "Taehyun Ko", "venue": null, "publisher": null, "abstract": "Real-time autonomous path planning is a critical capability in unmanned aerial vehicle (UAV) operations, especially in complex environments that involve both static and dynamic obstacles. This study proposes a dual-layer unmanned mobility framework that integrates dynamic obstacle avoidance based on data communication with static obstacle avoidance based on vision. The data communication-based layer utilizes the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm to process real-time position and velocity data from the Ground Control System (GCS), thereby reducing collision risks and enabling safe route planning in multi-UAV operations. The vision-based layer utilizes a depth camera to detect and avoid previously unknown or unpredictable obstacles, enabling real-time trajectory adjustments without relying on pre-mapped data. The dual-layer UAS operation system underwent a rigorous multi-phase validation process. Initially, the system was validated through Software-in-the-Loop (SITL) simulations conducted using Microsoft’s AirSim platform, which provided a high-fidelity environment for realistic training and performance assessment. SITL enabled effective testing of decision-making algorithms in complex environments containing both static and dynamic obstacles. To further enhance the reliability of the proposed system and assess its performance under hardware constraints, Hardware-in-the-Loop (HITL) testing was subsequently implemented as an intermediate verification step. The HITL configuration enabled real-time assessment of attitude and angular rate tracking through flight controllers, ensuring system stability and precise control before actual flight testing. Finally, actual flight tests were conducted at the drone test field of the Gwangju Institute of Science and Technology (GIST). Consistent results observed across SITL, HITL, and flight tests validated the system’s practicality, robustness, and applicability to real-world UAV operations in complex obstacle environments. This dual-layer hybrid framework demonstrates the effective integration of data communication and vision-based strategies, enabling reliable and efficient UAV navigation in complex environments. The findings support the potential of this system for advanced UAV applications in urban logistics, military missions, and disaster response operations.", "keywords": [ "Reinforcement learning", "Obstacle", "Computer science", "Artificial intelligence", "Obstacle avoidance", "Computer vision", "Mobile robot", "Robot", "Geography" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2514/6.2025-3686" }, { "id": "https://openalex.org/W4312429109", "doi": "10.46354/i3m.2022.hms.007", "title": "The use of autonomous coupling capable trailer to reduce the cost per delivery and increase profit for logistic companies: a simulative analysis", "year": 2022, "publication_date": "2022-01-01", "type": "conference-paper", "language": "en", "authors": [ "Elvezia Maria Cepolina", "Venkata Akhil Babu Malisetty", "Matteo Zoppi" ], "first_author": "Elvezia Maria Cepolina", "venue": "˜The œ... international conference on Harbor, maritime & multimodal logistics modelling and simulation", "publisher": null, "abstract": "Last-mile distribution causes more obstacles in urban areas all over the world. Increased volumes of packages to be delivered for customer homes is directly increasing the number of delivery vans movement inside the urban areas and thus add to congestion and negative health impact. Therefore, it is anything but surprising that in recent years many traditional delivery concepts on the last mile have been innovated. Among the most prominent are unmanned aerial vehicles (drones) and autonomous delivery robots taking over parcel delivery. In this paper we introduce the autonomous latching and unlatching concept for urban vehicle with trailer. Considering the fact that latching and unlatching operations generally happen in unstructured environments where obstacles are left lying around, the whole latching and unlatching process is divided into two phases, namely the trailer repositioning phase and the autonomous latching and unlatching phase. The benefits in last-mile logistics of using this autonomous trailer for unattended deliveries are evaluated in simulation with Anylogic software. Four different scenarios are simulated and compared: traditional vans without trailers; traditional vans to which trailers can be added manually; traditional vans with autonomous coupling capable trailers; autonomous vans with autonomous coupling capable trailers.", "keywords": [ "Trailer", "Last mile (transportation)", "Drone", "Computer science", "Mile", "Profit (economics)", "Transport engineering", "Engineering", "Computer network" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.46354/i3m.2022.hms.007" }, { "id": "https://openalex.org/W4411019380", "doi": "10.46254/an15.20250087", "title": "Optimization of Collaborative Truck-Drone-Subway Delivery for Urban Logistics", "year": 2025, "publication_date": "2025-02-18", "type": "conference-paper", "language": "en", "authors": [ "So Rim Han", "Byung Duk Song" ], "first_author": "So Rim Han", "venue": null, "publisher": null, "abstract": "The truck-drone hybrid delivery system has been proposed as an alternative for urban logistics due to its advantages in fast delivery, cost-efficiency, and environmental benefits. However, UAVs face limitations in battery capacity and payload, which make it challenging to meet the increasing demand for logistics services. Additionally, there are constraints in building new logistics facilities in urban areas. Underground logistics has emerged as an alternative solution to address these problems. By utilizing the subway network, the system can avoid urban traffic congestion and manage logistics flows efficiently. Moreover, it minimizes the cost of establishing new facilities by making the most of existing infrastructure. In this study, we propose a new urban delivery system that combines the existing truck-drone hybrid model with the subway network. The established subway network and stations are used to transport goods from suburban areas to urban areas, where they also function as urban logistics hubs. A truck and drones handle the last-mile delivery to customers from the subway stations. Both the truck and multiple drones operate independently; the truck does not act as a mothership for the drones, and they perform deliveries across multiple logistics depots. We developed a mathematical optimization model for a multi-depot, multi-trip vehicle routing problem with time windows. The developed model was validated through numerical experiments, demonstrating its practical applicability to urban delivery services.The truck-drone hybrid delivery system has been proposed as an alternative for urban logistics due to its advantages in fast delivery, cost-efficiency, and environmental benefits. However, UAVs face limitations in battery capacity and payload, which make it challenging to meet the increasing demand for logistics services. Additionally, there are constraints in building new logistics facilities in urban areas. Underground logistics has emerged as an alternative solution to address these problems. By utilizing the subway network, the system can avoid urban traffic congestion and manage logistics flows efficiently. Moreover, it minimizes the cost of establishing new facilities by making the most of existing infrastructure. In this study, we propose a new urban delivery system that combines the existing truck-drone hybrid model with the subway network. The established subway network and stations are used to transport goods from suburban areas to urban areas, where they also function as urban logistics hubs. A truck and drones handle the last-mile delivery to customers from the subway stations. Both the truck and multiple drones operate independently; the truck does not act as a mothership for the drones, and they perform deliveries across multiple logistics depots. We developed a mathematical optimization model for a multi-depot, multi-trip vehicle routing problem with time windows. The developed model was validated through numerical experiments, demonstrating its practical applicability to urban delivery services.", "keywords": [ "Truck", "Drone", "Transport engineering", "City logistics", "Computer science", "Aeronautics", "Engineering", "Automotive engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieomsociety.org/proceedings/singapore2025/87.pdf" }, { "id": "https://openalex.org/W4387780905", "doi": "10.1108/jhlscm-01-2023-0004", "title": "A multiobjective mathematical model for a humanitarian logistics multimodal transportation problem", "year": 2023, "publication_date": "2023-10-19", "type": "article", "language": "en", "authors": [ "Marisol S. Romero‐Mancilla", "Kenneth Edgar Hernandez-Ruiz", "Diana L. Huerta‐Muñoz" ], "first_author": "Marisol S. Romero‐Mancilla", "venue": "Journal of Humanitarian Logistics and Supply Chain Management", "publisher": "Emerald Publishing Limited", "abstract": "Purpose The purpose of this paper is to introduce a three-echelon multimodal transportation problem applied to a humanitarian logistic case study that occurred in Mexico. Design/methodology/approach This study develops a methodology combining a transshipment problem and an adaptation of the multidepot heterogeneous fleet vehicle routing problem to construct a mathematical model that incorporates the use of land-based vehicles and drones. The model was applied to the case study of the Earthquake on September 19, 2017, in Mexico, using the Gurobi optimization solver. Findings The results ratified the relevance of the study, showing an inverse relationship between transportation costs and delivery time; on the flip side, the model performed in a shorter CPU time with medium and small instances than with large instances. Research limitations/implications While the size of the instances limits the use of the model for big-scale problems, this approach manages to provide a good representation of a transportation network during a natural disaster using drones in the last-mile deliveries. Originality/value The present study contributes to a model that combines a vehicle routing problem with transshipment, multiple depots and a heterogeneous fleet including land-based vehicles and drones. There are multiple models present in the literature for these types of problems that incorporate the use of these transportation modes; however, to the best of the authors’ knowledge, there are still no proposals similar to this study.", "keywords": [ "Transshipment (information security)", "Computer science", "Solver", "Vehicle routing problem", "Operations research", "Drone", "Construct (python library)", "Routing (electronic design automation)", "Relevance (law)", "Paratransit", "Scale (ratio)", "Mathematical optimization" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.emerald.com/insight/content/doi/10.1108/JHLSCM-01-2023-0004/full/pdf?title=a-multiobjective-mathematical-model-for-a-humanitarian-logistics-multimodal-transportation-problem" }, { "id": "https://openalex.org/W4200357950", "doi": "10.1007/978-3-030-92666-3_7", "title": "Traveling Salesman Problem with Truck and Drones: A Case Study of Parcel Delivery in Hanoi", "year": 2021, "publication_date": "2021-12-07", "type": "conference-paper", "language": "en", "authors": [ "Quang Huy Vuong", "Giang Thi-Huong Dang", "Trung Do Quang", "Minh-Trien Pham" ], "first_author": "Quang Huy Vuong", "venue": "Lecture notes in networks and systems", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Job shop scheduling", "Truck", "Scheduling (production processes)", "Computer science", "Heuristic", "Operations research", "Mathematical optimization", "Engineering", "Computer network", "Artificial intelligence" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-030-92666-3_7" }, { "id": "https://openalex.org/W7167604213", "doi": "10.2139/ssrn.7075420", "title": "Coordinating Rail-Transit Freight and UAV Last-Mile Delivery under Train-Arrival Time-Base Constraints", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Liuying Fan", "Peng ZHAO", "Dewei Li", "Yonghao Yin", "Wang Duolong" ], "first_author": "Liuying Fan", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Payload (computing)", "Column generation", "Routing (electronic design automation)", "Transit (satellite)", "Task (project management)", "Scale (ratio)", "Resource (disambiguation)", "Vehicle routing problem", "Quality (philosophy)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.7075420" }, { "id": "https://openalex.org/W4225814429", "doi": "10.2139/ssrn.4006625", "title": "Freight-on-Transit for Urban Last-Mile Deliveries: A Strategic Planning Approach", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Diego Delle Donne", "Laurent Alfandari", "Claudia Archetti", "Ivana Ljubić" ], "first_author": "Diego Delle Donne", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Mile", "Transit (satellite)", "Last mile (transportation)", "Transport engineering", "Business", "Urban transit", "Operations management", "Environmental planning", "Geography", "Engineering", "Public transport" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4006625" }, { "id": "https://openalex.org/W7203714835", "doi": "10.1016/j.rico.2026.100800", "title": "A multi-objective optimization framework for integrating drone-based urban air mobility with ground logistics networks: toward sustainable and resilient last-mile delivery", "year": 2026, "publication_date": "2026-08-18", "type": "article", "language": "en", "authors": [ "Javad Javanmardnezhad", "Majid Mehrabi Delshad", "Farshad Kaveh", "Nasim Jafarnejad", "Majid Toulabi" ], "first_author": "Javad Javanmardnezhad", "venue": "Results in Control and Optimization", "publisher": "Elsevier BV", "abstract": "Rising urban population growth, congestion, and emissions pressures motivate urban air mobility (UAM) as a three-dimensional complement to ground logistics. This paper develops MO-UAMLN, a multi-objective mixed-integer linear program that jointly minimizes cost and emissions and maximizes disruption resilience for an integrated drone-ground vehicle network with vertiport infrastructure, solved via a novel Deep Reinforcement Learning-enhanced NSGA-III (DRL-NSGA-III) algorithm. In a Tehran case study (150 nodes, three distribution centers, eight vertiports), the integrated strategy cuts cost by 18.7% and emissions by 34.2% and raises expected disruption coverage to 88.0% versus single-mode baselines; DRL-NSGA-III significantly outperforms NSGA-II, NSGA-III, and MOEA/D (Holm-Bonferroni corrected p < 0.05, large effect sizes), and battery capacity, vertiport throughput, and demand density emerge as the dominant performance drivers. These results indicate that resilience arises from modal complementarity rather than redundant capacity, offering differentiated investment guidance for operators, planners, and policymakers. Findings rest on a single metropolitan case study and stylized assumptions, so generalization to other cities and real deployment conditions requires further validation.", "keywords": [ "Sustainability", "Key (lock)", "Work (physics)", "Air pollution" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.rico.2026.100800" }, { "id": "https://openalex.org/W7164463209", "doi": null, "title": "NOT IN MY BACKYARD? BYSTANDERS PRIVACY CALCULUS AND THE SOCIAL ACCEPTANCE OF DRONE DELIVERY", "year": 2026, "publication_date": "2026-08-15", "type": "article", "language": null, "authors": [ "Gianluca Maria Guazzo", "Pierangelo Rosati", "Theo Lynn" ], "first_author": "Gianluca Maria Guazzo", "venue": "Journal of the Association for Information Systems", "publisher": "Association for Information Systems", "abstract": "Drone delivery offers environmental and efficiency benefits for last-mile logistics but faces adoption barriers related to privacy concerns, particularly amongst individuals exposed to surveillance without direct transaction involvement (bystanders). This study examines how privacy perceptions and perceived benefits influence bystanders’ acceptance, drawing on privacy calculus theory. Survey data from 764 United States citizens were analyzed via structural equation modelling. Perceived intrusion significantly increases privacy concerns, negatively influencing both general and local acceptance. Perceived benefits strongly affect general acceptance but fail to overcome localized resistance, revealing a general–local acceptance asymmetry. General acceptance significantly predicts local acceptance, suggesting that cultivating favorable societal attitudes creates a pathway to community-level implementation. Digital privacy literacy moderates the privacy–acceptance relationship for general but not local acceptance. These findings advance technology acceptance theory by revealing how involuntary exposure contexts fundamentally alter privacy calculus, with implications for sustainable drone deployment in residential environments.", "keywords": [ "Drone", "Software deployment", "Technology acceptance model", "Perception", "Structural equation modeling", "Intrusion", "Information privacy", "Survey data collection" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1101&context=amcis2026" }, { "id": "https://openalex.org/W4410985851", "doi": "10.1109/tits.2025.3565821", "title": "Reliable Crowdsourced Last Mile Delivery: Blockchain-Enabled Framework With Feedback", "year": 2025, "publication_date": "2025-06-03", "type": "article", "language": "en", "authors": [ "Esraa Odeh", "Rabeb Mizouni", "Shakti Singh", "Hadi Otrok", "Jamal Bentahar" ], "first_author": "Esraa Odeh", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "This paper addresses the challenges of Last Mile Delivery (LMD) in crowdsourced platforms under time and budget constraints. LMD service providers face a continuous increase in demand with limited resources, such as workers and budgets. With tasks that vary in urgency, limited resources often lead to task failures. Furthermore, the increasing number of requesters and workers complicates the governance of the LMD platform, making it difficult to maintain credibility, integrity, and transparency. Current LMD solutions generally focus on route optimization and service acceleration, overlooking the challenge of combined time-critical and budget-constrained tasks. This creates the need for an agile, accelerated, and decentralized LMD framework that can 1) handle tasks instantly upon submission, 2) motivate successful completion based on urgency, and 3) compensate for tasks with deficient budgets to fortify long-term success and avoid failure due to constrained resources. For this purpose, this paper introduces the first Blockchain Hybrid Crowdsourced Auction-based LMD framework (BHCA-LMD), which is designed to effectively manage time and budget constraints. Built on-chain for transparency and decentralization, the framework uses drones and ground vehicles as a hybrid delivery mode for their capabilities in speeding up deliveries. BHCA-LMD incorporates an auctioning system to alleviate failures due to limited budgets, with a feedback mechanism to prevent entities from abusing the platform’s profit for their benefit, ensuring the credibility and reliability of the framework. The evaluation shows an on-time task completion rate of up to 74% with the presence of malicious behavior and a 15% lower gas consumption compared to the closest benchmark.", "keywords": [ "Blockchain", "Mile", "Crowdsourcing", "Last mile (transportation)", "Computer science", "Computer security", "World Wide Web", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2025.3565821" }, { "id": "https://openalex.org/W4412409198", "doi": "10.29121/ijetmr.v10.i12.2023.1642", "title": "E-COMMERCE AND THE EVOLUTION OF LAST-MILE DELIVERY: MEETING CUSTOMER EXPECTATIONS", "year": 2023, "publication_date": "2023-12-19", "type": "article", "language": "en", "authors": [ "Prakash Divakaran", "Vandana Mishra Chaturvedi" ], "first_author": "Prakash Divakaran", "venue": "International Journal of Engineering Technologies and Management Research", "publisher": "Granthaalayah Publications and Printers", "abstract": "E-commerce has transformed retail, offering customers ease and accessibility like never before. However, the last-mile delivery, the product's last leg from the distribution center to the customer's doorstep, has become a major hurdle for e-commerce enterprises. This abstract examines how e-commerce businesses are adapting to shifting consumer expectations in last-mile delivery. The abstract opens with e-commerce's fast expansion and influence on conventional retail methods. It underlines the trend toward online buying, which increases demand for efficient and rapid delivery services. The abstract then discusses last-mile delivery and consumer satisfaction. Delivery speed, adaptability, openness, and sustainability affect client expectations. The abstract also discusses last-mile delivery improvements. Drones, autonomous trucks, and smart lockers improve delivery efficiency and convenience. Crowd shipping, which uses local resources to improve last-mile operations, is also examined. The abstract highlights e-commerce enterprises' last-mile delivery issues. It covers urban congestion, unsuccessful deliveries, refunds, and transportation environmental effect. To satisfy client expectations, sustainable and eco-friendly delivery options are needed. Finally, the abstract emphasizes customer-centric last-mile delivery. Real-time monitoring, proactive communication, and customizable delivery choices improve customer experience. To maximize last-mile operations, e-commerce enterprises, logistics providers, and local stakeholders should collaborate. This abstract illuminates e-commerce last-mile delivery. It emphasizes the necessity of satisfying consumer expectations in this key phase of the delivery process and gives insights into the methods and technologies used by e-commerce enterprises to improve last-mile delivery and customer happiness.", "keywords": [ "Mile", "Last mile (transportation)", "Business", "Mobile commerce", "Marketing", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.granthaalayahpublication.org/ijetmr-ojms/ijetmr/article/download/1642/1361" }, { "id": "https://openalex.org/W7164420815", "doi": "10.1016/j.jclepro.2026.148735", "title": "Modelling the performance of emerging last-mile modes in 90 European pedestrian zones", "year": 2026, "publication_date": "2026-06-01", "type": "article", "language": "en", "authors": [ "Ada Garus", "Andromachi Mourtzouchou", "Konstantinos Mattas", "Biagio Ciuffo" ], "first_author": "Ada Garus", "venue": "Journal of Cleaner Production", "publisher": "Elsevier BV", "abstract": "This article compares the operational performance and sustainability of drones, autonomous delivery robots (ADRs), and electric cargo e-bikes through a simulation framework developed for pedestrian zones in 90 European cities. For each city, 200 parcels were assigned to evaluate mode-specific routing, energy use, cost, and service performance. Multi-criteria decision analysis (MCDA) was used to incorporate stakeholder perspectives. E-bikes combine the lowest energy demand with the low unit cost. ADRs offer the quietest, most space-efficient ground operation, halving drone energy use while matching bike cost, though their pedestrian speed lengthens service time. Drones deliver the shortest point-to-point travel time, 6–11 % quicker than bikes, but at higher externalities. Stakeholder-weighted MCDA scores average 0.83 for bikes, 0.61 for ADRs and 0.18 for drones, placing each mode first in one core attribute: overall sustainability (bike), low-impact night delivery (ADR) and urgent response (drone). The findings suggest policy mixes that fund cargo-bike infrastructure for routine flows, license ADR fleets for quiet off-peak distribution, and reserve drones for time-critical or topographically constrained drops. Such differentiated deployment can support decarbonisation, protect pedestrian comfort and maintain service quality in Europe's historic urban cores.", "keywords": [ "Pedestrian", "Mode (computer interface)", "Work (physics)", "Key (lock)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.jclepro.2026.148735" }, { "id": "https://openalex.org/W4220705843", "doi": "10.2139/ssrn.4065319", "title": "A Multi-Objective Coverage Optimization for Zero-Emission Autonomous Drone Delivery Charging Station Planning", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Mo ElSayed", "Ahmed Foda", "Moataz Mohamed" ], "first_author": "Mo ElSayed", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Zero (linguistics)", "Computer science", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4065319" }, { "id": "https://openalex.org/W7213473149", "doi": "10.1016/j.jclepro.2026.148735", "title": "Modelling the Performance of Emerging Last-Mile Modes in 90 European Pedestrian Zones", "year": 2025, "publication_date": "2025-12-02", "type": "article", "language": "en", "authors": [ "GARUS Ada", "MOURTZOUCHOU Andromachi", "MATTAS Konstantinos", "CIUFFO Biagio" ], "first_author": "GARUS Ada", "venue": "Joint Research Centre (European Commission)", "publisher": "European Commission", "abstract": null, "keywords": [ "Drone", "Sustainability", "Pedestrian", "Service (business)", "Software deployment", "License", "Stakeholder", "Matching (statistics)", "Multiple-criteria decision analysis" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://publications.jrc.ec.europa.eu/repository/handle/JRC145018" }, { "id": "https://openalex.org/W7163700132", "doi": "10.1016/j.trpro.2026.04.022", "title": "Reliability Based-model for Optimizing Routing of Truck-drone Delivery System", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": "en", "authors": [ "Ahmed Ghaithan", "Awsan Moahmmed", "Ahmed M. Attia", "Mohamed Noomane Darghouth" ], "first_author": "Ahmed Ghaithan", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "This study develops a reliability-based optimization model for routing of truck-drone delivery systems, where trucks transport goods from a central warehouse to depots and drones perform last-mile deliveries. Drone failures are modeled as exponentially distributed events that may result in partial or complete loss of customer demand. An optimization model is formulated to identify feasible routes that minimize expected demand loss and optimizes truck depot assignments to ensure overall system reliability. A demonstrated example with two depots, three drones, two trucks, and six customers was conducted. Initially, 41 feasible paths were evaluated. Then, three paths were determined with a minimum expected loss of 0.1999, with a total travel time of 50.207 minutes. When optimizing for travel time, only one depot was selected to serve all the six customers using two drones, yielding a total travel time of 46.55 minutes and an expected loss of 0.2179. The results demonstrate that considering reliability of the delivery system significantly influence the routing decisions.", "keywords": [ "Reliability (semiconductor)", "Truck", "Routing (electronic design automation)", "Vehicle routing problem", "Travel time", "Depot" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trpro.2026.04.022" }, { "id": "https://openalex.org/W4395470813", "doi": "10.1504/ijor.2024.10063707", "title": "Bi-objective multiple drones and trucks combined operation parcel delivery", "year": 2024, "publication_date": "2024-01-01", "type": "article", "language": "en", "authors": [ "Rohit Titiyal", "Shalabh Singh", "Bhawesh Sah", "Sonia Singh" ], "first_author": "Rohit Titiyal", "venue": "International Journal of Operational Research", "publisher": "Inderscience Publishers", "abstract": "Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.", "keywords": [ "Drone", "Truck", "Computer science", "Environmental science", "Operations research", "Transport engineering", "Automotive engineering", "Mathematics", "Engineering" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1504/ijor.2024.10063707" }, { "id": "https://openalex.org/W4285269729", "doi": "10.1504/ijmor.2022.10047093", "title": "Determining the Optimal Parcel Delivery Method Using One Drone and One Truck", "year": 2022, "publication_date": "2022-01-01", "type": "article", "language": "en", "authors": [ "Kazuki Satoh", "Hiroshi Morita" ], "first_author": "Kazuki Satoh", "venue": "International Journal of Mathematics in Operational Research", "publisher": "Inderscience Publishers", "abstract": "Delivering parcels using a combination of drones and trucks represents a promising new package delivery method.In previous studies, several truck/drone delivery planning problems and their solutions have been proposed.However, little research has been done to determine which delivery method is most appropriate.The reason for this is that it is difficult to obtain an exact solution for such problems, and thus the accuracy of the solutions is an issue.In this study, we propose an accurate solution procedure for the flying sidekick travelling salesman problem (FSTSP) and the parallel drone scheduling travelling salesman problem (PDSTSP), and establish which delivery method is most suitable based on the solutions obtained.", "keywords": [ "Truck", "Drone", "Computer science", "Operations research", "Automotive engineering", "Mathematics", "Engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1504/ijmor.2022.10047093" }, { "id": "https://openalex.org/W7161506482", "doi": "10.1504/ijor.2026.153571", "title": "Bi-objective multiple drones and trucks combined operation parcel delivery", "year": 2026, "publication_date": "2026-01-01", "type": "article", "language": "en", "authors": [ "Bhawesh Sah", "Shalabh Singh", "Rohit Titiyal", "Sonia Singh" ], "first_author": "Bhawesh Sah", "venue": "International Journal of Operational Research", "publisher": "Inderscience Publishers", "abstract": null, "keywords": [ "Drone", "Truck" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1504/ijor.2026.153571" }, { "id": "https://openalex.org/W4412623559", "doi": "10.1109/tsc.2025.3592374", "title": "Wind-Aware Service Provisioning Strategy for Multi-Package Drone Delivery", "year": 2025, "publication_date": "2025-01-01", "type": "article", "language": "en", "authors": [ "Xu Jia", "Hao nan Liu", "Xiao Liu", "Azadeh Ghari Neiat", "Xuejun Li", "Yun Jin Yang" ], "first_author": "Xu Jia", "venue": "IEEE Transactions on Services Computing", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "In recent years, drone delivery has drawn significant attention for its promising potential in solving the last-mile delivery problem. As a novel service paradigm, Drone-as-a-Service (DaaS) is emerging as an effective way to address service provisioning problems within complex delivery networks. However, existing DaaS composition frameworks often fail to consider the sharing of delivery services and are not applicable to multi-package drone delivery tasks. Meanwhile, as one of the most critical real-world environmental factors for drones, the impact of dynamic wind conditions is not adequately considered by existing studies. This may lead to Quality of Service (QoS) degradation of delivery services. To address the above issues, in this paper, we propose a wind-aware service provisioning strategy for multi-package drone delivery. Given the advantages of Edge Computing (EC) in handling such dynamic factors due to its low latency and high reliability, we first establish a spatio-temporal DaaS model based on service sharing according to the edge-based drone delivery system. Then, we propose a novel wind-aware drone delivery service provisioning strategy for multi-package delivery to minimize energy consumption of drones. The proposed strategy consists of two phases: service sharing and service composition. In the service sharing phase, the service sharing plan is generated by an improved genetic algorithm. In the service composition phase, the edge server dynamically generates the service composition plan through our proposed policy iteration based DaaS composition method. Experimental results using real delivery network and wind data demonstrate that our strategy is able to reduce delivery energy consumption of drone by about 10.1%.", "keywords": [ "Computer science", "Drone", "Provisioning", "Service (business)", "Computer network" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tsc.2025.3592374" }, { "id": "https://openalex.org/W7162519162", "doi": "10.1002/net.70051", "title": "Multi‐Objective Route Optimization for Drone Deliveries Integrated With Public Transportation", "year": 2026, "publication_date": "2026-05-26", "type": "article", "language": "en", "authors": [ "Yong Peng", "Yue Yu", "Dennis Z. Yu", "Xiaojun Yang", "Chester Xiang", "Zhi Ren" ], "first_author": "Yong Peng", "venue": "Networks", "publisher": "Wiley", "abstract": "ABSTRACT To enhance delivery efficiency while supporting urban public transportation development, this study investigates a bus‐assisted drone delivery route optimization problem within the context of the low‐altitude economy. A multi‐objective optimization model is formulated to minimize both distribution cost and time. To solve this problem efficiently, we propose a non‐dominated sorting variable neighborhood search (NSVNS) algorithm. To validate the algorithm's performance, we conduct a dispersion analysis to assess its stability and demonstrate its superiority over NSGA‐II in solution diversity, distribution uniformity, and overall effectiveness. Additionally, experimental analysis confirms the effectiveness of the proposed neighborhood search operators. Finally, a case study is conducted based on Chongqing city's line 100 bus route and surrounding customer locations to derive optimal drone delivery routes. Sensitivity analysis indicates that increasing drone payload capacity has a more significant impact on delivery efficiency than extending drone range, providing insights for optimizing drone‐based urban logistics.", "keywords": [ "Drone", "Payload (computing)", "Context (archaeology)", "Sorting", "Sensitivity (control systems)", "Stability (learning theory)", "Public transport", "Optimization problem" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/net.70051" }, { "id": "https://openalex.org/W7172418196", "doi": "10.3390/app16157751", "title": "Research on Route Optimization for Truck–Drone Delivery Considering En Route Synchronization", "year": 2026, "publication_date": "2026-08-04", "type": "article", "language": "en", "authors": [ "Shukang Zheng", "Genhua Ma", "Hanpei Yang", "Zichen Du", "Ye Lu", "Yinjia Chen" ], "first_author": "Shukang Zheng", "venue": "Applied Sciences", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Truck–UAV collaborative delivery can improve last-mile logistics efficiency, but fixed-node rendezvous often causes waiting loss and service delay. To address this problem, this paper proposes a route optimization method integrating en route synchronization, pseudo-node insertion, and GAT-PPO. Pseudo-nodes are generated along truck travel arcs to provide flexible UAV recovery points, and a time-recursive simulation model is developed to evaluate makespan and total tardiness under soft time windows. In the proposed framework, GAT is used to capture spatial–temporal relationships among nodes, while PPO supports sequential routing decisions and UAV dispatch coordination. Experiments on Solomon VRPTW instances with clustered, random, and mixed customer distributions show that GAT-PPO achieves the shortest total travel distance, the lowest total tardiness, and the shortest completion time among Random, NN, NN+2-opt, MLP-PPO, ALNS, GA, and VNS. Ablation results further confirm the contributions of GAT, PPO, pseudo-node insertion, en route synchronization, and UAV collaboration. The results indicate that the proposed framework can effectively reduce synchronization waiting loss and improve the temporal efficiency of truck–UAV collaborative delivery.", "keywords": [ "Tardiness", "Vehicle routing problem", "Truck", "Synchronization (alternating current)", "Rendezvous", "Job shop scheduling" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2076-3417/16/15/7751/pdf?version=1785841117" }, { "id": "https://openalex.org/W7171930750", "doi": "10.1109/ccgrid68966.2026.00042", "title": "FedMO: Mobility-Aware Client Selection in Federated Learning for Drone Delivery Systems", "year": 2026, "publication_date": "2026-05-01", "type": "conference-paper", "language": null, "authors": [ "Yuan Jiang", "xiao liu", "jia xu", "Aiting Yao", "Frank Jiang", "Xuejun Li" ], "first_author": "Yuan Jiang", "venue": null, "publisher": null, "abstract": "Last mile delivery by drones is a core component of innovative logistics systems, relying heavily on AI models for essential operations such as path planning and object recognition. However, models trained on region specific data often experience significant performance degradation when deployed in unfamiliar environments due to geographic domain shifts. This limitation impedes the rapid deployment of logistics networks and hinders model adaptation. Federated Learning (FL), as a distributed machine learning paradigm, enables multiple clients with diverse data to collaborate in training a global model. Nevertheless, within Mobile Edge Computing (MEC) environments, FL faces critical challenges, including data bias, high drone mobility, and intermittent communication windows between drones and edge servers. This paper proposes FedMO, a mobility aware FL framework for drone based last mile delivery with edge cloud collaboration. FedMO introduces a novel algorithmic insight by treating the drone’s flight path as a unified proxy for both communication reliability and data distribution heterogeneity. The framework implements a synergistic three stage selection policy that jointly optimizes connectivity success, data value, and resource efficiency. This effectively transforms mobility from a disruption risk into a diversity enhancing asset. Experimental results using real world drone video datasets demonstrate that FedMO improves convergence speed by approximately 15% compared to baseline methods with only 30%-40% client selection. With equivalent client participation, FedMO achieves a 25% improvement in convergence speed over the FedAvg algorithm.", "keywords": [ "Selection (genetic algorithm)", "Drone", "Key (lock)", "Federated learning", "Client–server model" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.26187/deakin.33318204" }, { "id": "https://openalex.org/W7204930755", "doi": "10.1201/9781042017546-58", "title": "A Cost-Effective Autonomous Drone Delivery System with Ultrasonic-Based Real-Time Obstacle Avoidance", "year": 2026, "publication_date": "2026-09-01", "type": "book-chapter", "language": "en", "authors": [ "Yash N. Jagtap", "Sachin M. Bhosle", "Vishal Bhagwat" ], "first_author": "Yash N. Jagtap", "venue": null, "publisher": null, "abstract": "The rapid growth of e-commerce and on-demand logistics has intensified pressure on last-mile delivery systems, demanding solutions that are autonomous, efficient, safe, and cost-effective. Unmanned Aerial Vehicles (UAVs) offer strong potential, yet deployment remains limited by payload endurance, obstacle avoidance reliability, and the high cost of advanced sensing technologies. This paper presents the design and experimental validation of a cost-effective UAV delivery platform integrating low-cost ultrasonic sensing with Pixhawk ArduPilot navigation for real-time obstacle avoidance and autonomous package release. A lightweight Arduino-based co-processor processes matrix-filtered ultrasonic data to enable collision-aware navigation without significant cost, weight, or computational overhead. Field trials achieved a 15-minute flight time, 4.5 km operational range, and stable payload delivery up to 600 g, with a 93% obstacle avoidance success rate within 3 m. Comparative analysis shows a 60% sensor cost reduction and 35% weight decrease compared to LiDAR-equipped UAVs, making the system a practical option for scalable last-mile logistics. The study highlights the potential of low-cost sensing architectures to bridge the gap between simulation research and deployable UAV networks, with future work focusing on multi-sensor fusion and AI-based path planning for resilient autonomous logistics.", "keywords": [ "Obstacle avoidance", "Payload (computing)", "Software deployment", "Obstacle", "Bridge (graph theory)", "Drone", "Collision avoidance", "Motion planning", "Scalability" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1201/9781042017546-58" }, { "id": "https://openalex.org/W4415445326", "doi": "10.54254/2755-2721/2025.ld28117", "title": "Cooperative Control of Unmanned Aerial Vehicle (UAV) Swarms and Swarm Intelligence", "year": 2025, "publication_date": "2025-10-22", "type": "article", "language": null, "authors": [ "Ziyuan Huang" ], "first_author": "Ziyuan Huang", "venue": "Applied and Computational Engineering", "publisher": null, "abstract": "The rapid advancement of drone swarm technology offers immense potential in areas such as disaster relief and anti-flood efforts. However, in some cases, they still have many problems, for example, unexpected emergent behaviours, difficulty in chronic communication and cybersecurity problems. This paper aims to improve the gait and efficiency of cooperative drone swarms by developing an integrated framework that combines hybrid A*-based path planning, multiple-mode communication architectures, and a fault-tolerant control system. Besides, the paper also applies the energy-aware heuristics, dynamic obstacle prediction and decentralised consensus algorithms for real-time adaptation and strong coordination. The results show remarkable improvement in formation stability, enabling the task to be completed and work appropriately in a dynamic environment. In real-life situations, the paper can utilise this app in earthquake rescue missions and urban logistics organisations to demonstrate the system's expandability and adaptability. This research advances the field of drone swarm technology, utilising both civilian and defence applications. The paper also explores the ethics and sustainable design implications for future advancements.", "keywords": [ "Drone", "Swarm behaviour", "Obstacle", "Task (project management)", "Field (mathematics)", "Adaptation (eye)", "Swarm intelligence", "Control (management)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.ewadirect.com/proceedings/ace/article/view/28117/pdf" }, { "id": "https://openalex.org/W4413079596", "doi": "10.28948/ngumuh.1680127", "title": "A review of collaborative strategies in last-mile logistics from an urban sustainability perspective", "year": 2025, "publication_date": "2025-07-15", "type": "article", "language": "en", "authors": [ "Fatmanur Özer", "Neslihan Demirel" ], "first_author": "Fatmanur Özer", "venue": "Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi", "publisher": "Association of Food Technology, Turkey", "abstract": "In recent years, globalization, technological developments, and the growth of e-commerce transactions have increased the demand for logistics activities. Increasing demands affect logistics activities at all stages of supply chains, particularly the final stage, where delivery to customers occurs in urban areas. This stage, known as last-mile logistics, is not only the most expensive and inefficient part of supply chains, but also causes many problems, including increased freight mobility in urban areas, traffic congestion, parking issues, air and noise pollution, and carbon emissions. Reducing these economic and environmental costs is important for sustainable urban development. The sustainability of a city depends on its economic self-sufficiency, the living standards of its population under equal and fair conditions, and sensitive practices in environmental and waste management. Today, in addition to the traditional last-mile logistics practices of delivering the package to the customer's home/office, there are many new practices (delivery via parcel locker, drone delivery, robot delivery, micro-depot usage, urban consolidation center usage, pick-up/drop-off point, click-and-collect, crowd-sourcing, etc.) to overcome the mentioned drawbacks and manage the process more effectively and efficiently. Collaborative applications for these novel delivery methods are increasing day by day in order to minimize the costs of logistics service providers, facilitate customers' access to service, and thus improve customer satisfaction. In this study, we investigate different novel last-mile logistics methods in the literature and in practice that have been implemented with collaborative strategies. Among the 43 studies reviewed, urban consolidation centers, parcel lockers, and PUDO points emerged as the most frequently considered collaborative models. The advantages of the collaboration strategies and the barriers to their development are presented, and researchers, practitioners, and city managers are guided in developing new policies and strategies.", "keywords": [ "Last mile (transportation)", "Business", "Sustainability", "Traffic congestion", "Supply chain", "City logistics", "Transport engineering", "Marketing", "Engineering", "Mile" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dergipark.org.tr/en/download/article-file/4790404" }, { "id": "https://openalex.org/W7162815406", "doi": "10.1108/sasbe-10-2025-0599", "title": "A multi-objective matheuristic framework for sustainable truck-UAV last-mile delivery in smart urban built environments", "year": 2026, "publication_date": "2026-05-29", "type": "article", "language": "en", "authors": [ "Armin Mahmoodi", "Said M. Easa" ], "first_author": "Armin Mahmoodi", "venue": "Smart and Sustainable Built Environment", "publisher": "Emerald Publishing Limited", "abstract": "Purpose This study addresses the escalating challenges of last-mile logistics driven by e-commerce growth and sustainability requirements. Despite recent advances in truck-UAV delivery models, existing studies often treat cost, energy and risk objectives in isolation or rely on purely heuristic or purely exact solution methods. This study explores the integration of hybrid truck-UAV delivery systems as an innovative component of sustainable urban infrastructure, with a focus on jointly balancing cost, service time, energy consumption and safety risk. Design/methodology/approach A hybrid multi-objective matheuristic framework is proposed, combining a metaheuristic-based truck routing phase with a mixed-integer linear programming (MILP)-based UAV assignment and scheduling phase. This integration leverages the scalability of heuristics with the precision of mathematical programming to generate efficient Pareto-optimal solutions. Computational experiments were conducted on benchmark instances of up to 100 customers. Findings Results show that MILP-guided initialization accelerates convergence and improves solution diversity compared to purely heuristic approaches. Sensitivity analyses highlight that configurations with two UAVs per truck and moderate endurance achieve the most balanced performance across sustainability objectives, significantly reducing energy use and delivery risk. Practical implications The framework provides a scalable decision-support tool for logistics operators, urban planners and policymakers to design safe, efficient and climate-responsive last-mile delivery networks that align with sustainable urban development strategies. Social implications By incorporating sustainability and safety risk into the optimization process, the framework supports the transition towards resilient, inclusive and environmentally responsible delivery systems, directly contributing to the achievement of the United Nations sustainable development goals (SDGs). Originality/value To the best of the authors’ knowledge, this study is among the first to develop a multi-objective matheuristic that integrates exact and heuristic optimization methods for truck-UAV coordination in sustainable last-mile logistics. It advances both methodological innovation and practical relevance for the built environment, bridging operations research with urban sustainability.", "keywords": [ "Sustainability", "Scalability", "Heuristics", "Heuristic", "Energy consumption", "Benchmark (surveying)", "Scheduling (production processes)", "Vehicle routing problem" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1108/sasbe-10-2025-0599" }, { "id": "https://openalex.org/W7160440898", "doi": "10.1109/scse70081.2026.11499781", "title": "Medi-Fly: A Safety-Aware, IoT-Enabled Micro-Scale UAV Framework for Reliable Last-Mile Medical Delivery", "year": 2026, "publication_date": "2026-03-26", "type": "conference-paper", "language": null, "authors": [ "Kithusshand Raveendran", "Vigneswaran Vithiyasahar", "Gowrisha Karuneswaran", "Pradeep K. W. Abeygunawardhana" ], "first_author": "Kithusshand Raveendran", "venue": null, "publisher": null, "abstract": "Timely delivery of essential medical supplies remains a major challenge in rural and resource-constrained healthcare systems, where poor road access, terrain constraints, and transport delays can hinder rapid response. This paper presents Medi-Fly, a safety-aware, IoT-enabled UAV framework for short-range last-mile medical delivery. The proposed system is designed as a platform-agnostic cyber-physical architecture that integrates supervised autonomous flight, payload monitoring, telemetry logging, and safety-gated mission control within a reproducible deployment framework. Key operational features include pre-flight diagnostics, geofencing, authenticated telemetry, controlled payload release, and automated return-to-launch behavior. Medi-Fly is evaluated through controlled field trials using an industry-provided multirotor UAV platform, together with route-matched road transport baselines and targeted faultinjection tests. Experimental results show approximately 80% reductions in end-to-end delivery time over$1-2 \\text{km}$routes compared with road-based transport, while maintaining high mission success, stable payload handling, and robust fail-safe recovery under adverse conditions. Although the evaluation is conducted at a single deployment site, route distance, environmental conditions, and injected fault scenarios are varied to improve realism and reproducibility. The results demonstrate that field-validated, safety-gated medical UAV systems can provide reliable, auditable, and cost-efficient short-range healthcare logistics without dependence on infrastructure-intensive delivery models. These findings position Medi-Fly as a practical reference architecture for scalable drone-enabled medical delivery in underserved regions.", "keywords": [ "Reliability (semiconductor)", "Key (lock)", "Component (thermodynamics)", "Field (mathematics)", "Measure (data warehouse)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/scse70081.2026.11499781" }, { "id": "https://openalex.org/W3154440371", "doi": "10.12958/1817-3772-2020-4(62)-85-96", "title": "Development of the Logistics 4.0 Concept in the Digital Economy", "year": 2020, "publication_date": "2020-01-01", "type": "article", "language": "en", "authors": [ "Трушкіна Наталія Валеріївна", "Henryk Dźwigoł", "Olena R. Serhieieva", "Yu. Shkrygun" ], "first_author": "Трушкіна Наталія Валеріївна", "venue": "Economic Herald of the Donbas", "publisher": null, "abstract": "The transition to a digital economy is becoming a key driver of GDP growth. This is due not only to the effect obtained from the automation of existing processes, but also from the introduction of new, breakthrough business models and technologies, including digital platforms, digital ecosystems, in-depth analytics of big data, Industry 4.0, Logistics 4.0. At the same time, digital transformation is seen as a radical change in the complex of business processes, from product development to customer service, as well as the introduction of modern digital technologies in the organization of business processes in enterprises. The purpose of the article is to analysis the features and trends of organizing logistics activities in the context of digital transformation of business processes; research of the main prerequisites for the formation of the Logistics 4.0 concept; determination of priority directions for its further development in the context of Industry 4.0. Based on the generalization of scientific approaches, the definition of the concept of \"Logistics 4.0\" has been clarified, which means the modern paradigm of managing logistic (material, financial, information, transport) flows and organizing a complex of logistics activities (purchase and delivery of material resources, warehousing, production, stock formation, recycling of industrial waste, customer service, transportation and sale of finished products) using breakthrough digital technologies and information systems. The priority areas of organizing the logistics activities of enterprises using digital technologies include the following: multichannel logistics; logistics marketplaces; rethinking the use of packaging; mass personalization; Silver Economy (new services for older clients and new opportunities for older workers); sustainable logistics; sharing economy; multi-supply; customer experience; smart containerization; big data analytics; augmented and virtual reality; cloud service applications and APIs; Internet of Things; robotics and automation; new generation wireless communication; blockchain; Artificial Intelligence; unmanned aerial vehicles or \"drones\"; 3D printing; unmanned vehicles; quantum computing; supergrid logistics; space logistics; the use of digital platforms that unite customers and transport and logistics companies (the parties can enter into digital contracts, exchange transport booking requests and electronic documents, control the delivery of goods in real time). All this can help to reduce costs by optimizing procurement; decrease in personnel costs and decrease in labour costs as a result of automation; reduction of errors in logistics; optimization of the supply process; efficient warehouse management; forecasting shipments; creation of optimal routes; operational planning of loads and control of delivery times; ensuring product delivery on time, improving customer loyalty; optimal interaction with customers on the \"last mile\".", "keywords": [ "Digital transformation", "Business", "Context (archaeology)", "Process management", "Digital economy", "Integrated logistics support", "Information technology", "Business model", "Computer science", "Knowledge management", "Industrial organization", "Marketing" ], "cited_by_count": 16, "is_retracted": false, "is_paratext": false, "open_access_url": "http://evd.luguniv.edu.ua/index.php/evd/article/download/206/207" }, { "id": "https://openalex.org/W7172170778", "doi": "10.5281/zenodo.21746000", "title": "Last-Mile Drug Distribution to Underserved Communities : A Review of Barriers and Intervention Models", "year": 2022, "publication_date": "2022-12-20", "type": "article", "language": null, "authors": [ "Cindy Serwaa Asiedu", "Alice Adwubi Asiedu" ], "first_author": "Cindy Serwaa Asiedu", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "The final segment of the pharmaceutical distribution chain is where supply systems most often fail underserved communities, leaving essential medicines available at regional level yet absent at the point of care. This review consolidates the documented barriers to effective last-mile delivery and the intervention models developed in response, and it situates both within the geography of physical access that defines the problem. The barriers examined include weak transport infrastructure, unreliable inventory data, recurring stockout and overstock cycles, insufficient last-mile financing, workforce constraints, and the distinct challenges of reaching remote and conflict-affected populations. The review then synthesizes evidence on intervention models, including community health worker distribution, mobile and outreach delivery, third-party logistics partnerships, drone and alternative-transport pilots, vendor-managed inventory, and integrated commodity campaigns. Each model is assessed for reported strengths, limitations, scalability, and enabling conditions, with particular attention to how lessons from large-scale campaign distribution can inform routine supply and to the sustainability of donor-initiated models after transition to government control. The synthesis concludes that no single model succeeds in isolation, and that context-matched, hybrid approaches paired with stronger data systems offer the most dependable route to equitable access. Outstanding evidence gaps and implementation priorities are set out to guide future work.", "keywords": [ "Outreach", "Distribution (mathematics)", "Intervention (counseling)", "Supply chain", "Government (linguistics)", "Workforce", "Sustainability", "Matching (statistics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.21746000" }, { "id": "https://openalex.org/W7118373616", "doi": "10.54989/msd-2025-0017", "title": "Delivering the Undeliverable: Fast Fashion, Last-Mile Logistics, and the Myth of Sustainable Consumption", "year": 2025, "publication_date": "2025-12-31", "type": "article", "language": "en", "authors": [ "Gilles Paché" ], "first_author": "Gilles Paché", "venue": "Management of Sustainable Development", "publisher": "Lucian Blaga University of Sibiu", "abstract": "At a time when ultra-fast delivery, especially same-day delivery, has become a benchmark for overconsumption, last-mile logistics exposes fundamental tensions between operational performance and environmental and social sustainability. The rapid expansion of fast fashion, fuelled by platforms such as Shein and Temu, demonstrates that speed and efficiency generate apparent gains while aggravating urban congestion, increasing carbon emissions, and intensifying pressure on delivery workers. Technological solutions, including drones, autonomous vehicles, automated hubs, and artificial intelligence, often create the illusion of sustainable progress, yet the rebound effect neutralizes individual benefits and encourages even more frequent and fragmented consumption. Conventional approaches that focus solely on optimizing flows fail to address the structural drivers of overconsumption. This position paper advocates systemic rethinking of last-mile logistics, emphasizing the integration of sobriety, social equity, and durability into operational strategies. Deconsumption practices: pooling orders, extending product lifespans, promoting second-hand goods, and accepting longer delivery times, function as concrete levers for reducing delivery density while ensuring access to essential goods. Under this perspective, the last mile becomes a political and social arena, where the very conditions for sustainable consumption and urban well-being are being actively redefined, highlighting the limits of purely technical solutions.", "keywords": [ "Consumption (sociology)", "Position (finance)", "Product (mathematics)", "Function (biology)", "Sustainable development", "Pooling", "Sustainable consumption", "Production (economics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://msdjournal.org/wp-content/uploads/9.-Delivering-the-Undeliverable-Fast-Fashion_pp.-133-144.pdf" }, { "id": "https://openalex.org/W7135330827", "doi": "10.82366/16", "title": "Routing of Hybrid Truck-Drone Delivery Systems: Mathematical Models and Solution Approaches", "year": 2023, "publication_date": "2023-03-01", "type": "dissertation", "language": "en", "authors": [ "Batool Madani" ], "first_author": "Batool Madani", "venue": "DSpace at AUS (American University of Sharjah)", "publisher": "American University of Sharjah", "abstract": "With the continuous growth of e-commerce, the responsibility of logistics providers for solving last mile delivery challenges is surging. The last mile delivery is the most polluting, most expensive, and least efficient part of the e-commerce supply chain. Therefore, logistics providers seek new solutions to improve delivery operations continuously. Drone advancements have paved the way for several applications in the field of logistics. However, restrictions such as battery and payload capacity have restricted the effective operational use of drones in many practical applications. To assist toward alleviating these operational limitations, several hybrid delivery models incorporating one or more drones launched from a larger vehicle have emerged. A recent research avenue is to integrate drones with traditional delivery methods such as trucks to form a hybrid truck-drone delivery system. The hybrid truck-drone delivery system (HTDDS) has received significant attention in the literature, due to its new operational challenges and the interdependency between the vehicles and their roles. Most of the literature considers a single customer visit per drone dispatch while launching and collecting the drone from customer nodes visited by the truck. In this research, three HTDDS models with drone multi-visits are introduced where the first model investigates the routing considerations of a truck acting as a moving depot for launching and collecting a drone at non-customer nodes. The second model permits flexibility in the drone’s launching and collecting operations by utilizing customer and non-customer nodes. The final model studies the extended version of the second model by employing several trucks in the delivery system as well as considering time-related constraints. For handling large instances of the proposed models, efficient solution approaches with novel strategies are introduced. In specific, a modified saving algorithm with neighborhood reduction schemes and variable neighborhood search frameworks with different neighborhood selection strategies are developed. In addition, a generalized nomenclature for defining the neighborhood structures is established, which can be applied to a variety of routing problems. Extensive computational analysis is performed to validate and test the performance of the proposed solution methods. Numerical findings indicate that the proposed solution methods outperform the basic approaches.", "keywords": [ "Mathematical model", "Routing (electronic design automation)", "Work (physics)", "Automation" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.82366/16" }, { "id": "https://openalex.org/W7140080570", "doi": "10.1016/j.procs.2026.02.240", "title": "The Last Mile of Online Retail in the Age of Sustainability: Insights into Austrian Customer Priorities", "year": 2026, "publication_date": "2026-01-01", "type": "conference-paper", "language": "en", "authors": [ "Robert L. Zimmermann", "Evelyn Rezek", "Patrick Brandtner" ], "first_author": "Robert L. Zimmermann", "venue": "Procedia Computer Science", "publisher": "Elsevier BV", "abstract": "This paper investigates which last mile delivery attributes most influence customer satisfaction in e-commerce and how retailers can prioritize them in ways that are both cost-efficient and environmentally responsible. A systematic literature review using Scopus, ScienceDirect, and Dimensions AI identified 16 recurring factors, ranging from delivery reliability and flexibility to ecological considerations, which formed the basis of an online questionnaire. The survey was conducted in July and August 2024 and yielded 130 valid responses from shoppers in the DACH region, primarily in Austria. The findings show that undamaged delivery, correct order fulfillment, punctuality, and data security are the most valued attributes, while sustainability-related aspects such as eco-friendly packaging and low-emission transport rank lowest. Most respondents prefer home delivery and are willing to wait longer or pay slightly more for flexible delivery slots. Nevertheless, 77% of participants expressed openness to drones or autonomous vehicles as a potential option for faster and more sustainable delivery. The paper concludes with practical recommendations, suggesting that retailers focus first on operational reliability and transparent pricing while gradually integrating green innovations.", "keywords": [ "Reliability (semiconductor)", "Flexibility (engineering)", "Last mile (transportation)", "Order (exchange)", "Openness to experience", "Customer satisfaction", "Drone", "Rank (graph theory)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.procs.2026.02.240" }, { "id": "https://openalex.org/W4403776512", "doi": "10.21203/rs.3.rs-5301607/v1", "title": "A study on optimizing the location selection problem for urban UAV distribution while accounting for obstacles", "year": 2024, "publication_date": "2024-10-25", "type": "preprint", "language": "en", "authors": [ "Sun Menghan", "Yu Yuance", "He Luyao", "Yong An Yang", "Yang Zailin" ], "first_author": "Sun Menghan", "venue": "Research Square", "publisher": null, "abstract": null, "keywords": [ "Selection (genetic algorithm)", "Distribution (mathematics)", "Computer science", "Geography", "Operations research", "Mathematics", "Artificial intelligence" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.21203/rs.3.rs-5301607/v1" }, { "id": "https://openalex.org/W7172129007", "doi": "10.5281/zenodo.21745999", "title": "Last-Mile Drug Distribution to Underserved Communities : A Review of Barriers and Intervention Models", "year": 2022, "publication_date": "2022-12-20", "type": "article", "language": null, "authors": [ "Cindy Serwaa Asiedu", "Alice Adwubi Asiedu" ], "first_author": "Cindy Serwaa Asiedu", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "The final segment of the pharmaceutical distribution chain is where supply systems most often fail underserved communities, leaving essential medicines available at regional level yet absent at the point of care. This review consolidates the documented barriers to effective last-mile delivery and the intervention models developed in response, and it situates both within the geography of physical access that defines the problem. The barriers examined include weak transport infrastructure, unreliable inventory data, recurring stockout and overstock cycles, insufficient last-mile financing, workforce constraints, and the distinct challenges of reaching remote and conflict-affected populations. The review then synthesizes evidence on intervention models, including community health worker distribution, mobile and outreach delivery, third-party logistics partnerships, drone and alternative-transport pilots, vendor-managed inventory, and integrated commodity campaigns. Each model is assessed for reported strengths, limitations, scalability, and enabling conditions, with particular attention to how lessons from large-scale campaign distribution can inform routine supply and to the sustainability of donor-initiated models after transition to government control. The synthesis concludes that no single model succeeds in isolation, and that context-matched, hybrid approaches paired with stronger data systems offer the most dependable route to equitable access. Outstanding evidence gaps and implementation priorities are set out to guide future work.", "keywords": [ "Outreach", "Distribution (mathematics)", "Intervention (counseling)", "Supply chain", "Government (linguistics)", "Workforce", "Sustainability", "Matching (statistics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.21745999" }, { "id": "https://openalex.org/W7204377369", "doi": null, "title": "New technologies and automation for last mile deliveries: Advantages, disadvantages and policy implications", "year": 2018, "publication_date": "2018-07-05", "type": "conference-paper", "language": "en", "authors": [ "Daniela Paddeu", "Graham Parkhurst" ], "first_author": "Daniela Paddeu", "venue": "UWE Research Repository (UWE Bristol)", "publisher": "University of the West of England", "abstract": "Urban freight transport is crucial to ensuring the economic vitality of a city. However, significant negative externalities arise from freight flows in an urban area (e.g. polluting emissions, contribution to congestion, noise, etc.). Alternatives to dispatcher-receiver delivery in large diesel vehicles, with lower external costs, have been proposed over the past decades. The most popular of these alternatives is the Urban Consolidation Centre (UCC), which replaces Heavy Good Vehicles with a smaller number of lighter vehicles, which may be electrically powered, by means of transhipment centre outside the urban area. However, there is a major concern about the financial sustainability of this type of scheme, which usually needs public funding support to cover operational costs. Hence, the paper explores to what extent other solutions for last-mile based on new technologies (i.e. autonomous vehicles, 3D printing and drones) to replace or integrate with current transport systems in urban areas might increase the viability of the UCC approach. A review of current and future developments in automated freight transport systems is undertaken. Due to the complexity of evaluating emerging technologies and forecasting trends, the report integrates academic papers, technical reports from international projects and trials, and findings from market research. It is found that, despite the importance of automation for improving the efficiency and competitiveness of the urban freight sector, research evidence gaps exist related to the identification of competitive advantages for these new technologies, micro and macro-economic benefits, and the costs of those developments. It is concluded that, whilst there may be potential for automation in the UK urban freight sector to enhance welfare, particularly in the form of urban quality of life, policymakers will have a crucial role in defining new policies and regulations to foster and accelerate the introduction of such systems, whilst at the same time ensuring equity and ethics.", "keywords": [ "Emerging technologies", "Automation", "Sustainability", "Externality", "Consolidation (business)", "Truck", "Government (linguistics)", "Identification (biology)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://uwe-repository.worktribe.com/output/3145628" }, { "id": "https://openalex.org/W4410738105", "doi": "10.1109/tvt.2025.3573595", "title": "High-Efficiency Urban 3D Radio Map Estimation Based on Sparse Measurements", "year": 2025, "publication_date": "2025-05-26", "type": "article", "language": "en", "authors": [ "Xinwei Chen", "Xiaofeng Zhong", "Zijian Zhang", "Linglong Dai", "Shidong Zhou" ], "first_author": "Xinwei Chen", "venue": "IEEE Transactions on Vehicular Technology", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Recent widespread applications for unmanned aerial vehicles (UAVs) – from infrastructure inspection to urban logistics – have prompted an urgent need for high-accuracy three-dimensional (3D) radio maps. However, existing methods designed for two-dimensional radio maps face challenges of high measurement costs and limited data availability when extended to 3D scenarios. To tackle these challenges, we first build a real-world large-scale 3D radio map dataset, covering over 4.2 million$\\rm {{m}}^{3}$and over 4 thousand data points in complex urban environments. We propose a Gaussian Process Regression-based scheme for 3D radio map estimation, allowing us to realize more accurate map recovery with a lower RMSE than state-of-the-art schemes by over 2.5dB. To further enhance data efficiency, we propose two methods for training point selection, including an offline clustering-based method and an online maximum a posterior (MAP)-based method. Extensive experiments demonstrate that the proposed scheme not only achieves full-map recovery with only 2% of UAV measurements, but also sheds light on future studies on 3D radio maps.", "keywords": [ "Computer science", "Remote sensing", "Electronic engineering", "Artificial intelligence", "Engineering", "Geography" ], "cited_by_count": 13, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tvt.2025.3573595" }, { "id": "https://openalex.org/W4200002667", "doi": "10.1109/iros51168.2021.9636684", "title": "Combined Routing and Scheduling of Heterogeneous Transport and Service Agents", "year": 2021, "publication_date": "2021-09-27", "type": "conference-paper", "language": "en", "authors": [ "Saaketh R. Narayan", "James Paulos", "Steven W. Chen", "Sandeep Manjanna", "Vijay Kumar" ], "first_author": "Saaketh R. Narayan", "venue": "2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)", "publisher": null, "abstract": "This paper investigates servicing waypoints in a wide area using collaborative deployments of vehicles with heterogeneous range and mobility constraints. We formulate a joint planning problem for a single transport truck and multiple service drones in which the truck is constrained to a road and must deploy a team of range-constrained drones to visit waypoints. The need to deploy, collect, and redeploy drones over multiple flights introduces both route finding and scheduling aspects to this problem. We solve large problem instances by decoupling our approach into a service drone route finding phase and a transport truck scheduling phase. Numerical simulations explore the qualitative character of the driving schedule and the quantitative marginal value of adding additional drones to the team as a function of agent number and relative speed. The combination of road network constraints and range constraints make this problem especially relevant to wide area forestry, last-mile delivery, and ecological monitoring applications.", "keywords": [ "Drone", "Computer science", "Scheduling (production processes)", "Truck", "Operations research", "Schedule", "License", "Routing (electronic design automation)", "Distributed computing", "Computer network", "Transport engineering", "Engineering" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/iros51168.2021.9636684" }, { "id": "https://openalex.org/W7128374257", "doi": "10.5281/zenodo.18529387", "title": "Evaluating the Adoption of a Drone Delivery System for Emergency Obstetric Medicines in Rural Rwanda: An Intervention Study", "year": 2009, "publication_date": "2009-06-04", "type": "article", "language": "en", "authors": [ "Marie Aimee Uwase", "Jean de Dieu Uwimana" ], "first_author": "Marie Aimee Uwase", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Access to emergency obstetric medicines in rural Rwanda is hindered by geographical barriers and logistical constraints, contributing to high maternal mortality from preventable causes such as postpartum haemorrhage. This study evaluated the adoption of the 'VillageReach' drone delivery system for emergency obstetric medicines in hard-to-reach areas. Its objectives were to assess the system's operational feasibility, acceptance by healthcare workers, and impact on medicine availability at health centres. An intervention study was conducted. The intervention implemented a drone delivery network for uterotonics and other essential obstetric drugs. Data were collected through routine system monitoring, stock level audits at participating health centres, and semi-structured interviews with healthcare workers and logisticians. The drone system was integrated into the existing supply chain. Stock audits indicated a 40% reduction in stock-out days for key uterotonics at intervention sites compared to the pre-intervention period. Interviews revealed strong acceptance among healthcare workers, with increased reliability and reduced anxiety about shortages cited as key benefits. The drone delivery system proved to be a feasible and acceptable intervention to improve the availability of emergency obstetric medicines in rural Rwanda, addressing critical logistical gaps in the last-mile supply chain. Programme planners should consider scaling the drone delivery model to other remote regions. Further research is needed to evaluate the system's cost-effectiveness and its direct impact on clinical maternal outcomes. maternal health, drones, logistics, last-mile delivery, essential medicines, Rwanda, implementation research This study provides empirical evidence on the implementation of an unmanned aerial vehicle system for health commodity delivery in a low-resource setting, contributing to the literature on innovative last-mile logistics for maternal health.", "keywords": [ "Intervention (counseling)", "Drone", "Audit", "Health care", "Public health", "Rural health" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.18529387" }, { "id": "https://openalex.org/W7124155127", "doi": "10.1109/codit66093.2025.11321659", "title": "Sustainable Last-Mile Delivery with Autonomous Aerial Vehicles and Autonomous Terrestrial Robots: a Case Study *", "year": 2025, "publication_date": "2025-07-15", "type": "conference-paper", "language": null, "authors": [ "Angelina Krendeleva", "Bartolomeo Silvestri", "Maria Pia Fanti", "Agostino Marcello Mangini" ], "first_author": "Angelina Krendeleva", "venue": null, "publisher": null, "abstract": "Last-mile delivery remains one of the key challenges in modern logistics, especially given the growing demand for fast and efficient transport solutions. This study evaluates two delivery strategies: autonomous aerial drone delivery with one parcel per trip and autonomous terrestrial robot delivery with the ability to transport multiple parcels per trip. Simulation modeling is used to analyze the economic, environmental, and social aspects of these methods. The study applies Simulation of Urban Mobility software to simulate the performance of autonomous terrestrial robots in an urban environment taking into account traffic, and a mathematical model to evaluate the performance of autonomous aerial drones. Three scenarios are considered: (1) drone-only delivery, (2) robot-only delivery, and (3) mixed fleet approach combining both methods. The results show that autonomous aerial drones provide faster delivery, but autonomous terrestrial robots are a more economical and environmentally sustainable solution. The hybrid approach strikes a balance between efficiency and cost, optimizing last-mile logistics. This study contributes to the development of sustainable urban delivery models and provides practical recommendations to policy makers and logistics companies.", "keywords": [ "Drone", "Robot", "Key (lock)", "Software", "Autonomous system (mathematics)", "Autonomous robot", "Motion planning" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/codit66093.2025.11321659" }, { "id": "https://openalex.org/W7117110014", "doi": "10.2139/ssrn.5964221", "title": "Physics-aware Truck and Drone Delivery Planning Using Optimization & Machine Learning", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": null, "authors": [ "Yineng Sun", "Armin R. Fügenschuh", "Vikrant Vaze" ], "first_author": "Yineng Sun", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Trajectory", "Truck", "Key (lock)", "Plan (archaeology)", "Motion planning", "Train", "Kinematics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5964221" }, { "id": "https://openalex.org/W7132149277", "doi": null, "title": "Algorithms for multi-robot systems on the cooperative exploration & last-mile delivery problems", "year": 2020, "publication_date": "2020-01-01", "type": "dissertation", "language": "en", "authors": [ "Fernando Ropero Pastor" ], "first_author": "Fernando Ropero Pastor", "venue": "e_Buah", "publisher": null, "abstract": "La aparición de los vehículos aéreos no tripulados (UAVs) y de los vehículos terrestres no tripulados (UGVs) ha llevado a la comunidad científica a enfrentarse a problemas ideando paradigmas de cooperación con UGVs y UAVs. Sin embargo, no suele ser trivial determinar si la cooperación entre UGVs y UAVs es adecuada para un determinado problema. Por esta razón, en esta tesis, investigamos un paradigma particular de cooperación UGV-UAV en dos problemas de la literatura, y proponemos un controlador autónomo para probarlo en escenarios simulados. Primero, formulamos un problema particular de exploración cooperativa que consiste en alcanzar un conjunto de puntos de destino en un área de exploración a gran escala. Este problema define al UGV como una estación de carga móvil para transportar el UAV a través de diferentes lugares desde donde el UAV puede alcanzar los puntos de destino. Por consiguiente, proponemos el algoritmo TERRA para resolverlo. Este algoritmo se destaca por dividir el problema de exploración en cinco subproblemas, en los que cada subproblema se resuelve en una etapa particular del algoritmo. Debido a la explosión de la entrega de paquetes en las empresas de comercio electrónico, formulamos también una generalización del conocido problema de la entrega en la última milla. En este caso, el UGV actúa como una estación de carga móvil que transporta a los paquetes y a los UAVs, y estos se encargan de entregarlos. De esta manera, seguimos la estrategia de división descrita por TERRA, y proponemos el algoritmo COURIER. Este algoritmo replica las cuatro primeras etapas de TERRA, pero construye una nueva quinta etapa para producir un plan de tareas que resuelva el problema. Para evaluar el paradigma de cooperación UGV-UAV en escenarios simulados, proponemos el controlador autónomo ARIES. Este controlador sigue un enfoque jerárquico descentralizado de líder-seguidor para integrar cualquier paradigma de cooperación de manera distribuida. Ambos algoritmos han sido caracterizados para identificar los aspectos relevantes del paradigma de cooperación en los problemas relacionados. Además, ambos demuestran un gran rendimiento del paradigma de cooperación en tales problemas, y al igual que el controlador autónomo, revelan un gran potencial para futuras aplicaciones reales.", "keywords": [], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/10017/51208" }, { "id": "https://openalex.org/W7161121184", "doi": "10.1007/s10669-026-10092-z", "title": "Optimizing urban logistics: a boundary-based drone–truck combined operations method", "year": 2026, "publication_date": "2026-05-14", "type": "article", "language": "en", "authors": [ "Akash Mallepula", "Bhawesh Sah" ], "first_author": "Akash Mallepula", "venue": "Environment Systems & Decisions", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Scalability", "Truck", "Dependency (UML)", "Traffic congestion", "Sustainability", "Cluster analysis" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10669-026-10092-z" }, { "id": "https://openalex.org/W4417439593", "doi": "10.48550/arxiv.2507.16259", "title": "Physics-aware Truck and Drone Delivery Planning Using Optimization & Machine Learning", "year": 2025, "publication_date": "2025-07-22", "type": "preprint", "language": "en", "authors": [ "Sun, Yineng", "Armin R. Fügenschuh", "Vikrant Vaze" ], "first_author": "Sun, Yineng", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "Combining an energy-efficient drone with a high-capacity truck for last-mile package delivery can benefit operators and customers by reducing delivery times and environmental impact. However, directly integrating drone flight dynamics into the combinatorially hard truck route planning problem is challenging. Simplified models that ignore drone flight physics can lead to suboptimal delivery plans. We propose an integrated formulation for the joint problem of truck route and drone trajectory planning and a new end-to-end solution approach that combines optimization and machine learning to generate high-quality solutions in practical online runtimes. Our solution method trains neural network predictors based on offline solutions to the drone trajectory optimization problem instances to approximate drone flight times, and uses these approximations to optimize the overall truck-and-drone delivery plan by augmenting an existing order-first-split-second heuristic. Our method explicitly incorporates key kinematics and energy equations in drone trajectory optimization, and thereby outperforms state-of-the-art benchmarks that ignore drone flight physics. Extensive experimentation using synthetic datasets and real-world case studies shows that the integration of drone trajectories into package delivery planning substantially improves system performance in terms of tour duration and drone energy consumption. Our modeling and computational framework can help delivery planners achieve annual savings worth millions of dollars while also benefiting the environment.", "keywords": [ "Drone", "Trajectory", "Truck", "Key (lock)", "Plan (archaeology)", "Train", "Kinematics", "Motion planning" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2507.16259" }, { "id": "https://openalex.org/W7115820256", "doi": "10.71548/15576", "title": "AUTONOMOUS UNMANNED AERIAL VEHICLES (UAVs): SYSTEM DESIGN & OPTIMIZATION", "year": 2022, "publication_date": "2022-01-01", "type": "dissertation", "language": "en", "authors": [ "Mohamed, ElSayed" ], "first_author": "Mohamed, ElSayed", "venue": "MacSphere (McMaster University)", "publisher": "McMaster University", "abstract": "The introduction of electric autonomous Unmanned Arial Vehicles (UAVs) in cities is considered the ultimate disruptive sustainable technological solution due to the promised speed, affordability, and significant greenhouse gas (GHG) emission reductions. The integration of UAVs into the future smart city fabric offers a wide range of applications. In particular, UAVs are ideal for last-mile operation, which is expected to reduce delivery costs, GHG emissions, and delivery time compared to light trucks and other traditional delivery methods. As UAVs operate in the city airspace, and with the current generation of older cities, several technological challenges arise with the anticipated proliferation of heterogeneous UAV fleets in low-altitude airspace of dense urban areas. Being a fairly new disruptive technology with no real-world operation data, the literature only considers a few of the system design parameters and often disregards the impact of other essential parameters such as Kinematics and airspace policies. This leads to significant uncertainty in the estimated UAV energy consumption, ranges, and emissions yielding inaccurate conclusions regarding the full system design predilections. Therefore, an effective UAV system design should strive to understand the broad spectrum of parameters’ impacts to optimize the integration and operation. Towards that end, this research aims at investigating the different UAV system design parameters and their intertwined impacts on operation efficiency to obtain accurate system optimization results. The research utilized several datasets for the delivery demand and digital-twin city model data of Toronto, Ontario, Canada. The research employed a state-of-the-art flexible energy use model for UAVs calibrated to experimental measurements to generate a minimum-energy trajectory along with several proposed novel airspace discretization, trajectory optimization, and charging infrastructure allocation optimization models. In this respect, this dissertation quantified the impact of airspace policies, discretization, and trajectory generation on the energy consumption of UAVs. Furthermore, it unveiled the operation uncertainties and their implications on the cost, emissions, and allocated charging infrastructure demand. Unlike the UAV literature, our research included all system design parameters and their impact on the performance metrics. The dissertation also proposes a novel combined airspace discretization and trajectory generation algorithm for optimal UAV energy consumption, airspace capacity maximization, airspace traffic control, and off-grid solar charging station allocation. For instance, it is found that UAV deployment with carefully tailored airspace policies in delivery could reduce GHG emissions in the freight sector by up to 35% compared to EVs. Furthermore, the research highlighted how building integrated photovoltaic BIPV upgrades with associated buildings can eliminate GHG emissions and significantly reduce the decarbonization price through associated savings and excess generated electricity. Overall, this research presents a unique contribution to the knowledge of UAV research for practitioners, policymakers, and academia.", "keywords": [ "Truck", "Greenhouse gas", "Systems design", "Drone", "System integration", "Range (aeronautics)", "Efficient energy use", "Energy (signal processing)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.71548/15576" }, { "id": "https://openalex.org/W7164138785", "doi": "10.2139/ssrn.6910773", "title": "Simulating City-Scale Drone Delivery: Noise Pollution and Population Exposure in London", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Volodymyr Shevchenko", "Cheriesse Bema", "Leslie‐Anne Duvic‐Paoli", "Martim Brandão" ], "first_author": "Volodymyr Shevchenko", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Noise pollution", "Population", "Routing (electronic design automation)", "Noise (video)", "Global Positioning System", "Motion planning" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.6910773" }, { "id": "https://openalex.org/W7128388986", "doi": "10.5281/zenodo.18529386", "title": "Evaluating the Adoption of a Drone Delivery System for Emergency Obstetric Medicines in Rural Rwanda: An Intervention Study", "year": 2009, "publication_date": "2009-06-04", "type": "article", "language": "en", "authors": [ "Marie Aimee Uwase", "Jean de Dieu Uwimana" ], "first_author": "Marie Aimee Uwase", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Access to emergency obstetric medicines in rural Rwanda is hindered by geographical barriers and logistical constraints, contributing to high maternal mortality from preventable causes such as postpartum haemorrhage. This study evaluated the adoption of the 'VillageReach' drone delivery system for emergency obstetric medicines in hard-to-reach areas. Its objectives were to assess the system's operational feasibility, acceptance by healthcare workers, and impact on medicine availability at health centres. An intervention study was conducted. The intervention implemented a drone delivery network for uterotonics and other essential obstetric drugs. Data were collected through routine system monitoring, stock level audits at participating health centres, and semi-structured interviews with healthcare workers and logisticians. The drone system was integrated into the existing supply chain. Stock audits indicated a 40% reduction in stock-out days for key uterotonics at intervention sites compared to the pre-intervention period. Interviews revealed strong acceptance among healthcare workers, with increased reliability and reduced anxiety about shortages cited as key benefits. The drone delivery system proved to be a feasible and acceptable intervention to improve the availability of emergency obstetric medicines in rural Rwanda, addressing critical logistical gaps in the last-mile supply chain. Programme planners should consider scaling the drone delivery model to other remote regions. Further research is needed to evaluate the system's cost-effectiveness and its direct impact on clinical maternal outcomes. maternal health, drones, logistics, last-mile delivery, essential medicines, Rwanda, implementation research This study provides empirical evidence on the implementation of an unmanned aerial vehicle system for health commodity delivery in a low-resource setting, contributing to the literature on innovative last-mile logistics for maternal health.", "keywords": [ "Intervention (counseling)", "Drone", "Audit", "Health care", "Public health", "Rural health" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.18529386" }, { "id": "https://openalex.org/W7116878081", "doi": "10.2139/ssrn.5957006", "title": "Coordinated Drone Delivery via Hybrid Training: From Optimization to Reinforcement Learning", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": null, "authors": [ "Lizhi Bi", "B. Shuai", "Zhanru Liu", "Yichen Sun" ], "first_author": "Lizhi Bi", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Reinforcement learning", "Drone", "Markov decision process", "Time horizon", "Heuristic", "Resource allocation", "Mode (computer interface)", "Hybrid system", "Architecture" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5957006" }, { "id": "https://openalex.org/W4412916116", "doi": "10.2139/ssrn.5359555", "title": "Physics-aware Truck and Drone Delivery Planning Using Optimization & Machine Learning", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": "en", "authors": [ "Yineng Sun", "Armin R. Fügenschuh", "Vikrant Vaze" ], "first_author": "Yineng Sun", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Computer science", "Engineering", "Automotive engineering", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5359555" }, { "id": "https://openalex.org/W7127080930", "doi": "10.1109/ieem63636.2025.11357717", "title": "Optimizing Last-Mile Delivery Efficiency through a Multi-Vehicle and MultiArea Collaboration Model", "year": 2025, "publication_date": "2025-12-07", "type": "conference-paper", "language": null, "authors": [ "S. H. Lu", "C. C. Chang", "R. Raj" ], "first_author": "S. H. Lu", "venue": null, "publisher": null, "abstract": "The rapid growth of e-commerce has heightened the need for logistics companies to improve package delivery efficiency. In conventional delivery models, vehicle speed is often constrained by urban speed regulations and the difficulty of locating available parking spaces. Unlike previous studies that focus on trucks collaborating with a single type of auxiliary vehicle, this paper explores a multivehicle approach by integrating a truck with two distinct types of delivery vehicles—a drone and a robot—and determining the most suitable deployment scenario for each. To address this problem, a heuristic algorithm is proposed to solve the Multiple Area and Multiple Vehicle Traveling Salesman Problem (TSP-MAMV). Experimental results show that deploying robots for deliveries in high-density urban areas can significantly enhance efficiency, while in lower- density regions, drones outperform robots in executing last- mile deliveries.", "keywords": [ "Drone", "Truck", "Heuristic", "Software deployment", "Travelling salesman problem", "Focus (optics)", "Robot" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/ieem63636.2025.11357717" }, { "id": "https://openalex.org/W7163416220", "doi": "10.5281/zenodo.20491476", "title": "Dataset for Last-Mile Delivery Energy Consumption: Insights from a Simulation-Based Analysis", "year": 2026, "publication_date": "2026-06-01", "type": "dataset", "language": "en", "authors": [ "Michał Kłodawski", "Konrad Lewczuk", "Jiajing Gao" ], "first_author": "Michał Kłodawski", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "The purpose of this dataset is to enable the replication and interpretation of the simulation research results presented in the article: Kłodawski, M., Lewczuk, K., & Gao, J. (2025). Last-Mile Delivery Energy Consumption: Insights from a Simulation-Based Analysis. In Q. Xiaobo, W. Zhang, Y. Liu, & Y. Yiping (Eds.), Proceedings of the 14th Asia-Pacific Conference on Transportation and the Environment (APTE 2025), pp. 176-187. Atlantis Press. https://doi.org/10.2991/978-94-6463-972-8_17 The article presents a simulation-based analysis of energy consumption in last-mile delivery systems. The analysed variants include:- courier-to-customer delivery,- courier-to-parcel-locker delivery with customers collecting packages,- courier-to-parcel-locker delivery with drones assigned to parcel lockers,- courier-to-parcel-locker delivery with drones operating in the whole service area. The dataset contains input data and simulation output tables used to analyse delivery time, distance, energy consumption and CO2 emissions for the considered last-mile delivery variants. The dataset was created as part of the E-Laas project (Energy optimal urban logistics As A Service).Project implemented as part of the call ERA-NET Cofund Urban Accessibility and Connectivity (ENUAC China Call) organized by JPI Urban Europe and the National Natural Science Foundation of China (NSFC). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875022. E-Laas project is carried out in an international consortium. Project coordinator in Europe: Chalmers University of Technology (Sweden), project coordinator in China: Shanghai University (China), consortium members: Tsinghua University (China), Warsaw University of Technology (Poland), cooperation partners: Stockholms stad, Trafikkontoret (Sweden), ParkUnload (Spain), Metropolis GZM (Poland), Shanghai Urban-Rural Construction and Transportation Department (China), Volvo Group Trucks Technology and Operations (Sweden).- The Chinese part of the project is funded by National Natural Science Foundation of China.- The Swedish part of the project is funded by Swedish Energy Agency.- The Polish part of the project is funded by the National Science Centre, Poland (project no. 2022/04/Y/ST8/00134). The value of the co-financing is PLN 878,107.00. Project duration 27/04/2023 - 26/04/2026 (36 months).", "keywords": [ "Energy consumption", "Drone", "China", "Consumption (sociology)", "Service (business)", "Integrated project delivery", "Efficient energy use" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.20491476" }, { "id": "https://openalex.org/W7167805261", "doi": "10.1016/j.trc.2026.105857", "title": "Coordinated drone delivery via hybrid training: From optimization to reinforcement learning", "year": 2026, "publication_date": "2026-07-09", "type": "article", "language": "en", "authors": [ "Lizhi Bi", "Bin Shuai", "Zhanru Liu", "Yichen Sun" ], "first_author": "Lizhi Bi", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Reinforcement learning", "Time horizon", "Flexibility (engineering)", "Speedup", "Inference", "Provisioning", "Integer (computer science)", "Artificial neural network", "Stochastic programming" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2026.105857" }, { "id": "https://openalex.org/W7214031425", "doi": "10.2139/ssrn.7507562", "title": "Hybrid Truck–Drone Delivery Systems: Optimization, Economic Viability, and Sustainability Challenges", "year": 2026, "publication_date": "2026-01-01", "type": "preprint", "language": null, "authors": [ "Farhood Farshadkhah", "Priyadarshi Nepal", "Abdur Rahman", "Mohammad Marufuzzaman", "Golam Kabir" ], "first_author": "Farhood Farshadkhah", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Sustainability", "Drone", "Scalability", "Framing (construction)", "Cost–benefit analysis", "Synchronization (alternating current)", "Energy system" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.7507562" }, { "id": "https://openalex.org/W7130531427", "doi": "10.1109/tits.2026.3660878", "title": "Bi-Level Optimization Framework for Urban Low-Altitude UAV Delivery Ensuring Target Level of Safety", "year": 2026, "publication_date": "2026-02-19", "type": "article", "language": null, "authors": [ "Bo Jiang", "Yichao Li", "Chenglong Li", "Yuan Zheng" ], "first_author": "Bo Jiang", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "In recent years, urban low-altitude UAV logistics has emerged as a pivotal solution for last-mile delivery. To enhance operational efficiency, it is essential to address the Coupled Task Allocation and Trajectory Optimization Problem (CTA-TOP) for heterogeneous UAVs. However, existing research, which often approaches this problem using multi-objective weight assignment methods, suffers from two primary shortcomings: (1) It overlooks the inherently multi-objective nature of the problem, where improper weight allocation leads to solutions that deviate from practical needs (e.g., low risk weights may ignore excessive local risks, while high weights unduly sacrifice efficiency). (2) Although ground risk is recognized as a fundamental constraint for Urban Air Mobility (UAM), weight-based optimization cannot guarantee that segment path risks consistently remain below the Target Level of Safety (TLS). To this end, this paper proposes a bi-level optimization framework based on improved algorithms: the TC-NSGA-III algorithm is employed for task allocation to minimize total ground risk, delivery time cost, and UAV workload balance, while the RG-FMT${}^{\\ast }$algorithm is used for trajectory planning to ensure path risk remains below the TLS. Simulation results demonstrate that the proposed RG-FMT${}^{\\ast }$algorithm achieves a 100% TLS compliance rate in trajectory planning with the shortest computation time. The overall framework significantly outperforms comparative methods across key metrics such as total risk and time cost. Further large-scale urban scenario simulations validate the algorithm’s generalization capability and scalability. This study provides an effective solution for safe and efficient coordinated scheduling in urban low-altitude logistics.", "keywords": [ "Trajectory", "Workload", "Scheduling (production processes)", "Key (lock)", "Task (project management)", "Computation", "Path (computing)", "Constraint (computer-aided design)" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2026.3660878" }, { "id": "https://openalex.org/W7163349315", "doi": "10.5281/zenodo.20491477", "title": "Dataset for Last-Mile Delivery Energy Consumption: Insights from a Simulation-Based Analysis", "year": 2026, "publication_date": "2026-06-01", "type": "dataset", "language": "en", "authors": [ "Michał Kłodawski", "Konrad Lewczuk", "Jiajing Gao" ], "first_author": "Michał Kłodawski", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "The purpose of this dataset is to enable the replication and interpretation of the simulation research results presented in the article: Kłodawski, M., Lewczuk, K., & Gao, J. (2025). Last-Mile Delivery Energy Consumption: Insights from a Simulation-Based Analysis. In Q. Xiaobo, W. Zhang, Y. Liu, & Y. Yiping (Eds.), Proceedings of the 14th Asia-Pacific Conference on Transportation and the Environment (APTE 2025), pp. 176-187. Atlantis Press. https://doi.org/10.2991/978-94-6463-972-8_17 The article presents a simulation-based analysis of energy consumption in last-mile delivery systems. The analysed variants include:- courier-to-customer delivery,- courier-to-parcel-locker delivery with customers collecting packages,- courier-to-parcel-locker delivery with drones assigned to parcel lockers,- courier-to-parcel-locker delivery with drones operating in the whole service area. The dataset contains input data and simulation output tables used to analyse delivery time, distance, energy consumption and CO2 emissions for the considered last-mile delivery variants. The dataset was created as part of the E-Laas project (Energy optimal urban logistics As A Service).Project implemented as part of the call ERA-NET Cofund Urban Accessibility and Connectivity (ENUAC China Call) organized by JPI Urban Europe and the National Natural Science Foundation of China (NSFC). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875022. E-Laas project is carried out in an international consortium. Project coordinator in Europe: Chalmers University of Technology (Sweden), project coordinator in China: Shanghai University (China), consortium members: Tsinghua University (China), Warsaw University of Technology (Poland), cooperation partners: Stockholms stad, Trafikkontoret (Sweden), ParkUnload (Spain), Metropolis GZM (Poland), Shanghai Urban-Rural Construction and Transportation Department (China), Volvo Group Trucks Technology and Operations (Sweden).- The Chinese part of the project is funded by National Natural Science Foundation of China.- The Swedish part of the project is funded by Swedish Energy Agency.- The Polish part of the project is funded by the National Science Centre, Poland (project no. 2022/04/Y/ST8/00134). The value of the co-financing is PLN 878,107.00. Project duration 27/04/2023 - 26/04/2026 (36 months).", "keywords": [ "Energy consumption", "Drone", "China", "Consumption (sociology)", "Service (business)", "Integrated project delivery", "Efficient energy use" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5281/zenodo.20491477" }, { "id": "https://openalex.org/W7208821683", "doi": "10.1007/978-3-032-27371-0_38", "title": "Technology Acceptance Theories in the Context of Autonomous Drone Delivery: Integrating Trust and Sustainability Perspectives", "year": 2026, "publication_date": "2026-01-01", "type": "conference-paper", "language": "en", "authors": [ "Ilona Pawełoszek", "Marko VAN DEVENTER" ], "first_author": "Ilona Pawełoszek", "venue": "Lecture notes in networks and systems", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Drone", "Context (archaeology)", "Sustainability", "Key (lock)", "Agency (philosophy)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-032-27371-0_38" }, { "id": "https://openalex.org/W3185356688", "doi": null, "title": "Improving Drone-based Parcel Delivery in a Delivery System at its Capacity Limit.", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Niclas zum Felde", "Michael Köhler-Bußmeier", "Jan O. Sudeikat" ], "first_author": "Niclas zum Felde", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Drone", "Limit (mathematics)", "Delivery system", "Computer science", "Environmental science", "Engineering", "Mathematics", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "http://ceur-ws.org/Vol-2907/paper2.pdf" }, { "id": "https://openalex.org/W7204167298", "doi": "10.1016/j.tre.2026.105182", "title": "Energy-aware drone-based parcel delivery problem with multi-charging mode availability", "year": 2026, "publication_date": "2026-08-25", "type": "article", "language": "en", "authors": [ "Yanfang Ma", "Mengdi Yuan", "Zhinan Wu", "Rui Qiu", "Feng Li" ], "first_author": "Yanfang Ma", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Mode (computer interface)", "Reliability (semiconductor)", "Mathematical model", "Key (lock)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2026.105182" }, { "id": "https://openalex.org/W4412653023", "doi": "10.1145/3749847", "title": "Near-Linear Time Scheduling for Drone-Based Parcel Delivery from a Warehouse", "year": 2025, "publication_date": "2025-07-26", "type": "article", "language": "en", "authors": [ "L. Sunil Chandran", "Rishikesh R. Gajjala", "Shravan Mehra", "Saladi Rahul" ], "first_author": "L. Sunil Chandran", "venue": "ACM Journal on Autonomous Transportation Systems", "publisher": "Association for Computing Machinery", "abstract": "We consider the problem where a warehouse has multiple drones and wants to deliver parcels to several customers. Each drone picks a parcel from the warehouse, delivers it and returns to the warehouse. The speeds and battery lives of the drones could be different and due to the limited battery life, each drone has a bounded range in which it can deliver parcels. The goal is to assign parcels to the drones so that the time taken to deliver all the parcels is minimized. This turns out to be an NP-hard problem, and hence, the focus of this article is to design a fast approximation algorithm. We do this by adapting the Longest Processing Time First (LPT) heuristic, which is a classical heuristic for the fundamental problem of uniform machine scheduling to the Drones Warehouse Problem (DWP) , which is a natural generalization of the uniform machine scheduling problem. We prove that the natural approach of solving this problem via the LPT heuristic has an approximation factor of ϕ, where ϕ ≈ 1.62 is the golden ratio. LPT heuristic was first considered by Gonzalez et al. (SIAM J. Comput. 6(1):155–166, 1977) . Since then, extensive work has been done to improve the approximation factor of the LPT heuristic. However, all known implementations of the LPT heuristic take O(mn) time, where m is the number of machines and n is the number of jobs. In this work, we come up with the first near-linear time implementation for LPT both for DWP and Uniform Scheduling. Specifically, the running time is O((n+m) (log 2 m +log n )). Somewhat surprisingly, the result is obtained by mapping the problem to dynamic maintenance of lower envelope lines, which has been well-studied in the computational geometry community.", "keywords": [ "Drone", "Warehouse", "Scheduling (production processes)", "Computer science", "Operations research", "Real-time computing", "Operations management", "Business", "Engineering", "Marketing", "Biology" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dl.acm.org/doi/pdf/10.1145/3749847" }, { "id": "https://openalex.org/W4388483191", "doi": "10.1109/ase56229.2023.00020", "title": "EXPRESS 2.0: An Intelligent Service Management Framework for AIoT Systems in the Edge", "year": 2023, "publication_date": "2023-09-11", "type": "conference-paper", "language": "en", "authors": [ "Xu Jia", "Xiao Liu", "Wuzhen Pan", "Xuejun Li", "Aiting Yao", "Yun Jin Yang" ], "first_author": "Xu Jia", "venue": null, "publisher": null, "abstract": "AIoT (Artificial Intelligence of Things) which integrates AI and IoT has received rapidly growing interest from the software engineering community in recent years. It is crucial to design scalable, efficient, and reliable software solutions for large-scale AIoT systems in edge computing environments. However, the lack of effective service management including the support for service collaboration, AI application, and data security in the edge, has seriously limited the development of AIoT systems. To seal this gap, we propose EXPRESS 2.0 which is an intelligent service management framework for AI oT in the edge. Specifically, on top of the existing EXPRESS platform, EXPRESS 2.0 includes the intelligent service collaboration management module, AI application management module, and data security management module. To demonstrate the effectiveness of the framework, we design and implement a last-mile delivery system using both UAVs (Unmanned Aerial Vehicles) and UGVs (Unmanned Ground Vehicles). The EXPRESS 2.0 is open-sourced at https://github.com/ISEC-AHU/EXPRESS2.0. A video demonstration of EXPRESS 2.0 is at https://youtu.be/GHKD_VvJD88.", "keywords": [ "Computer science", "Scalability", "Edge computing", "Service (business)", "Enhanced Data Rates for GSM Evolution", "Service management", "Management system", "Software engineering", "Software", "Computer security", "Database", "Operating system" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://figshare.com/articles/conference_contribution/EXPRESS_2_0_An_Intelligent_Service_Management_Framework_for_AIoT_Systems_in_the_Edge/24814782" }, { "id": "https://openalex.org/W4410539586", "doi": "10.51244/ijrsi.2025.12040124", "title": "Advancing Autonomous Last-Mile Delivery: A Techno-Economic Comparison of U.S. and Chinese Innovations", "year": 2025, "publication_date": "2025-01-01", "type": "article", "language": "en", "authors": [ "Olakunle Abimbola Kumuyi" ], "first_author": "Olakunle Abimbola Kumuyi", "venue": "International journal of research and scientific innovation", "publisher": null, "abstract": "This study conducts a comparative economic analysis of autonomous vehicle (AV) adoption in last-mile delivery between China and the United States, with a focus on both aerial (drone) and ground-based systems. Drawing on case studies, empirical data from 2018 to 2024, and regulatory assessments, the research evaluates how differing national contexts shape AV implementation outcomes. China’s rapid integration of AV technologies is facilitated by centralized policy support, cohesive regulations, and smart infrastructure, enabling businesses of all sizes to reduce costs, scale efficiently, and achieve substantial delivery speed improvements. Conversely, U.S. businesses face higher adoption barriers due to fragmented regulatory environments, slower infrastructure development, and scalability limitations, particularly for small and medium-sized enterprises. Despite these hurdles, technological innovation in the U.S. shows promising potential. The study finds that while drones enhance speed and sustainability, ground vehicles offer superior payload capacity and route flexibility, with hybrid models emerging as the most economically viable. Policy harmonization, infrastructure investment, and SME access to AV solutions are identified as critical for unlocking economic benefits across both markets. This research offers actionable insights for stakeholders aiming to accelerate the future of autonomous last-mile logistics.", "keywords": [ "Mile", "Last mile (transportation)", "Engineering", "Business", "Geography" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.51244/ijrsi.2025.12040124" }, { "id": "https://openalex.org/W7124829458", "doi": "10.3390/s26020653", "title": "Automatic Grasping System and Hybrid Controller Towards Multi-Drone Parcel Delivery", "year": 2026, "publication_date": "2026-01-18", "type": "article", "language": "en", "authors": [ "Bruno J. Guerreiro", "Francisco Azevedo", "Paulo Oliveira", "Rita Cunha" ], "first_author": "Bruno J. Guerreiro", "venue": "Sensors", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "This paper presents the development of an autonomous grasping mechanism for drone-based parcel delivery systems towards developing capabilities for in-flight package transfer. The approach integrates a mechanical gripper fitted with sensors and a pose estimation method for parcels, all coordinated through a hybrid Model Predictive Control (MPC) architecture. The gripper's mechanical structure and prototype are developed using 3D printing technology for both the main framework and gear components. A hybrid dynamical model is formulated that integrates the gripper mechanics with simplified drone dynamics, capturing distinct operational phases including package acquisition, transport, and release. The hybrid MPC framework computes reference trajectories for both the gripper arm configuration and the drone's spatial path toward designated target positions. Experimental validation is conducted using the operational gripper prototype and pose estimation system, while drone behavior is represented through simulation.", "keywords": [ "Drone", "Controller (irrigation)", "Hybrid system", "Grippers", "Scheme (mathematics)", "Path (computing)", "Mechanism (biology)", "Model predictive control" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1424-8220/26/2/653/pdf?version=1768731693" }, { "id": "https://openalex.org/W4313202696", "doi": "10.5281/zenodo.7488496", "title": "Lifespan-prolonging Dual Battery System Online Operation Scheduling for In-city Drone Delivery", "year": 2022, "publication_date": "2022-12-28", "type": "article", "language": "en", "authors": [ "Yuan Yiliang", "Xie Jiahang" ], "first_author": "Yuan Yiliang", "venue": "Zenodo (CERN European Organization for Nuclear Research)", "publisher": "European Organization for Nuclear Research", "abstract": "Delivery conducted by drones is a significant role in in-city delivery and last-mile delivery cooperated with trucks, owing to their fast speed and economy. Despite all the remarkable advantages of the participation of drones in last-mile delivery, more challenges are introduced. Since drones are powered by batteries, battery lifetime and the associated replacement cost are one of the main hindrances to more cost-efficient drone applications in delivery. In this work, the lifetime-prolonging dual battery scheduling problem for drone operation is introduced. This problem is motivated by the real-world case where drones are utilized for healthcare delivery during the pandemic. As battery degradation induces the main cost in such application scenes, we propose a novel approach to make online decisions in the dual battery operation system to support drone flying tasks and reduce the cost of drone operation without future information concerning flying conditions. The dual battery consists of a new battery bank and a second-life battery bank, in which the scheduling can regulate the output of the new battery pack and thus extend its lifespan and meanwhile make full use of the abundant second-life battery resources. With the battery degradation model, the amortized operation cost curve including the battery reliability is derived. The online optimization algorithm is developed to solve the problem. Adopting the established dual battery schema, battery cost in the delivery system is reduced with new battery sustainable operation in the validation process.", "keywords": [ "Drone", "Scheduling (production processes)", "Dual (grammatical number)", "Battery (electricity)", "Computer science", "Engineering", "Operations management", "Power (physics)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://zenodo.org/record/7488496" }, { "id": "https://openalex.org/W4322622614", "doi": "10.1541/ieejeiss.143.332", "title": "A Look-ahead Search Method for Parcel Delivery Planning in Collaboration with Vehicle and Drone", "year": 2023, "publication_date": "2023-02-28", "type": "article", "language": "en", "authors": [ "Satoru Hori", "Norihisa Komoda", "Takenao Ohkawa" ], "first_author": "Satoru Hori", "venue": "IEEJ Transactions on Electronics Information and Systems", "publisher": null, "abstract": "A parcel delivery method combining a vehicle and a drone is proposed. In a parcel delivery business where delivery time windows exist, the delivery order is determined by considering both keeping the delivery time windows restriction and shorting the total delivery time. To solve this problem, firstly, an initial solution is obtained by looking ahead multiple route candidates and selecting the point that leads to the route with the largest number of packages that can be delivered during the specified time windows as the next destination. Then, the initial plan is successively improved. Through simulation evaluation, it is confirmed that the proposed method can increase the number of packages that can be delivered during the specified time windows and reduce delivery time compared to a method where an initial solution is greedily searched by using only next destinations' information.", "keywords": [ "Drone", "Computer science", "Plan (archaeology)", "Point (geometry)", "Delivery system", "Simulation", "Real-time computing", "Operations research", "Engineering", "Mathematics" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1541/ieejeiss.143.332" }, { "id": "https://openalex.org/W4313413601", "doi": "10.3390/drones7010022", "title": "Gusts Encountered by Flying Vehicles in Proximity to Buildings", "year": 2022, "publication_date": "2022-12-28", "type": "article", "language": "en", "authors": [ "Abdulghani Mohamed", "Matthew Marino", "Simon Watkins", "Justin Jaworski", "Anya R. Jones" ], "first_author": "Abdulghani Mohamed", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "There is a growing desire to operate Uncrewed Air Vehicles (UAVs) in urban environments for parcel delivery, and passenger-carrying air taxis for Advanced Air Mobility (AAM). The turbulent flows and gusts around buildings and other urban infrastructure can affect the steadiness and stability of such air vehicles by generating a highly transient relative flow field. Our aim is to review existing gust models, then consider gust encounters in the vicinity of buildings as experienced by flight trajectories over the roof of a nominally cuboid building in a suburban atmospheric boundary layer. Simplified models of fixed- and rotary-wing aircraft are used to illustrate the changes in lift and thrust experienced by flight around the building. The analysis showed that fixed-wing aircraft experienced a substantial increase in angle of attack over a relatively short period of time (<1 s) as they fly through the shear layer at a representative forward velocity, which can be well above typical stall angles. Due to the slow flight speeds required for landing and take-off, significant control authority of rotor systems is required to ensure safe operation due to the high disturbance effects caused by localized gusts from buildings and protruding structures. Currently there appears to be negligible certification or regulation for AAM systems to ensure safe operations when traversing building flow fields under windy conditions and it is hoped that the insights provided in this paper will assist with future certification and regulation.", "keywords": [ "Stall (fluid mechanics)", "Thrust vectoring", "Aircraft flight mechanics", "Traverse", "Lift (data mining)", "Aeronautics", "Aerospace engineering", "Downwash", "Marine engineering", "Wing", "Aviation", "Engineering" ], "cited_by_count": 70, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/7/1/22/pdf?version=1672217218" }, { "id": "https://openalex.org/W7160493427", "doi": "10.32479/irmm.23132", "title": "Smart Last-mile Delivery Systems: Technological Advances, Operational Strategies, and Future Directions", "year": 2026, "publication_date": "2026-05-08", "type": "article", "language": null, "authors": [ "Mohammad Shadab Hussain", "Shabana Shabana", "Amiya Bhaumik", "Oyyappan DURAIPANDI", "Shoaib Ansari" ], "first_author": "Mohammad Shadab Hussain", "venue": "International Review of Management and Marketing", "publisher": "EconJournals", "abstract": "The rapid expansion of e-commerce and on-demand services has transformed last-mile delivery into one of the most critical, complex, and cost-intensive components of modern supply chains. Traditional delivery models are increasingly unable to cope with rising customer expectations, urban congestion, environmental pressures, and operational inefficiencies. In response, smart last-mile delivery systems based on digital technologies, automation, and data-driven optimization have emerged as a promising solution. This study provides a comprehensive and systematic review of the literature on smart last-mile delivery by integrating technological advances, operational strategies, and sustainability perspectives. Using a structured systematic literature review and bibliometric analysis of Scopus-indexed publications from 2000 to 2026, this research examines the evolution, intellectual structure, and thematic trends of the field. The analysis reveals a sharp growth in scholarly output after 2017, reflecting the increasing strategic importance of last-mile logistics in global e-commerce and urban freight systems. Keyword co-occurrence, thematic clustering, and network analysis show that the field is primarily anchored in e-commerce, logistics, and supply chain management, with last-mile delivery emerging as the dominant operational challenge. Strong linkages are also observed with sustainability, artificial intelligence, digital transformation, and urban logistics, indicating a shift toward technology-enabled and environmentally responsible delivery solutions. The findings further highlight the growing role of artificial intelligence, the Internet of Things, autonomous vehicles, drones, smart lockers, and micro-fulfilment centers in improving routing efficiency, reducing delivery failures, lowering costs, and mitigating environmental impacts. At the same time, the review identifies significant research gaps, particularly in relation to developing economies, long-term sustainability impacts, regulatory frameworks, and socio-economic consequences of automation. By offering an integrated synthesis of technological, operational, and sustainability dimensions, this study contributes to a deeper understanding of smart last-mile delivery systems and provides a roadmap for future research and policy. The results support the development of more resilient, efficient, and sustainable last-mile logistics models in the digital economy.", "keywords": [ "Sustainability", "Thematic analysis", "Smart city", "Supply chain", "The Internet", "Field (mathematics)", "Systematic review", "Food delivery" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://econjournals.com/index.php/irmm/article/download/23132/10079" }, { "id": "https://openalex.org/W4327702529", "doi": "10.2514/1.d0320", "title": "Ground Crash Area Estimation of Quadrotor Aircraft Under Propulsion Failure", "year": 2023, "publication_date": "2023-03-17", "type": "article", "language": "en", "authors": [ "Mohd Hasrizam Che Man", "Anush Kumar Sivakumar", "Hu Haoliang", "Kin Huat Low" ], "first_author": "Mohd Hasrizam Che Man", "venue": "Journal of Air Transportation", "publisher": "American Institute of Aeronautics and Astronautics", "abstract": "Small unmanned aircraft systems or drones are expected to be used for different applications, such as parcel delivery, inspection, and aerial photography, in urban areas. However, drones usually use an electric system to power up the propulsion, communications, navigation, and flight control system, which means that it is not as reliable as the manned aircraft system and may result in failure during operation and then crash to the ground. At present, there is almost no extensive publication about the high-fidelity modeling used by drones to calculate the crash trajectory and point of crash. The experimental data for modeling and simulation verification of multirotor aircraft are limited. So far, crash trajectory prediction has been limited to point mass or ballistic methods, and these methods are usually only suitable for complete power failure and without any control system. This study intends to investigate the effects of different multirotor drones’ failure modes on its crash trajectory and crash area compared to the ballistic model by using ADAMS and MATLAB cosimulation methods. Conclusions from the study show the crash trajectory, flight distance, and impact speed of the drones under four failure modes, which are quite different from the ballistic trajectory. The findings can potentially contribute to better risk assessment of the multirotor drones for the urban environment operation.", "keywords": [ "Multirotor", "Crash", "Drone", "Trajectory", "Propulsion", "Aeronautics", "Computer science", "Engineering", "Aerospace engineering", "Simulation" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dr.ntu.edu.sg/bitstream/10356/167368/3/2022-04-D0320-Manuscript-Final.pdf" }, { "id": "https://openalex.org/W7127134108", "doi": "10.1145/3787256.3787269", "title": "Locker-based Drone Delivery with Battery Swapping Stations: A Joint Routing–Recharging Optimization", "year": 2025, "publication_date": "2025-11-21", "type": "conference-paper", "language": null, "authors": [ "Wushuang Wang", "Yiliu Tan", "Yu Li", "Maiko Shigeno" ], "first_author": "Wushuang Wang", "venue": null, "publisher": null, "abstract": "Against the backdrop of growing e-commerce demand and tightening labor constraints, drone delivery has emerged as a promising alternative for scalable and automated last-mile logistics. This paper examines a Locker-based Drone Delivery system with Battery-Swapping Stations (LDDP), addressing a critical gap in prior research that overlooks the limitations of drone range and the practical role of battery infrastructure. We formalize the LDDP problem on a time-expanded network and develop a mixed-integer linear programming model that simultaneously optimizes drone routing, locker service sequencing, and battery-swapping operations under realistic operational constraints. To validate the proposed model, experiments are conducted using real-world geographic data from Tsukuba, Japan.", "keywords": [ "Drone", "Scalability", "Battery (electricity)", "Joint (building)", "Service (business)" ], "cited_by_count": 0, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1145/3787256.3787269" } ]