[ { "id": "https://openalex.org/W3157932358", "doi": "10.1109/access.2021.3077041", "title": "A Review on UAV Wireless Charging: Fundamentals, Applications, Charging Techniques and Standards", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Prithvi Krishna Chittoor", "Bharatiraja Chokkalingam", "Lucian Mihet‐Popa" ], "first_author": "Prithvi Krishna Chittoor", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Unmanned Aerial Vehicles (UAVs) are becoming increasingly popular for applications such as inspections, delivery, agriculture, surveillance, and many more. It is estimated that, by 2040, UAVs/drones will become a mainstream delivery channel to satisfy the growing demand for parcel delivery. Though the UAVs are gaining interest in civil applications, the future of UAV charging is facing a set of vital concerns and open research challenges. Considering the case of parcel delivery, handling countless drones and their charging will become complex and laborious. The need for non-contact based multi-device charging techniques will be crucial in saving time and human resources. To efficiently address this issue, Wireless Power Transmission (WPT) for UAVs is a promising technology for multi-drone charging and autonomous handling of multiple devices. In the literature of the past five years, limited surveys were conducted for wireless UAV charging. Moreover, vital problems such as coil weight constraints, comparison between existing charging techniques, shielding methods and many other key issues are not addressed. This motivates the author in conducting this review for addressing the crucial aspects of wireless UAV charging. Furthermore, this review provides a comprehensive comparative study on wireless charging's technical aspects conducted by prominent research laboratories, universities, and industries. The paper also discusses UAVs' history, UAVs structure, categories of UAVs, mathematical formulation of coil and WPT standards for safer operation.", "keywords": [ "Drone", "Inductive charging", "Computer science", "Wireless", "Key (lock)", "SAFER", "Telecommunications", "Risk analysis (engineering)", "Systems engineering", "Computer security", "Engineering", "Business" ], "cited_by_count": 265, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/9312710/09420719.pdf" }, { "id": "https://openalex.org/W4403794757", "doi": "10.1080/15568318.2024.2419378", "title": "Sustainable last mile logistics employing drones and e-bikes", "year": 2024, "publication_date": "2024-10-01", "type": "article", "language": "en", "authors": [ "Stephanie Santiago-Montaño", "Daniel F. Silva", "Alice E. Smith" ], "first_author": "Stephanie Santiago-Montaño", "venue": "International Journal of Sustainable Transportation", "publisher": "Taylor & Francis", "abstract": "Last mile delivery is an important and growing part of the supply chain that has a sizeable negative environmental impact. This paper considers more sustainable approaches to home-delivery that are pragmatic for many non-rural environments. We address the two-echelon, multi-trip, capacitated vehicle routing problem with home-delivery and optional self-pickup services using different combinations of drones, trucks, and electric-assisted bikes (i.e. e-bikes). In the proposed approach, parcels are transported from a depot to parcel lockers by either drones or trucks and are then delivered to customer locations by either e-bikes or trucks. The four approaches range from the most sustainable (drones then e-bikes) to partly green (drone then truck or truck then e-bike) to finally the traditional (truck then truck). We formulate a mathematical model that determines the vehicle routes to minimize the total cost, which consists of vehicle operational cost and operator wages. The four types of delivery networks are assessed and compared for both costs and emissions. Experimental results suggest that with a modest increase in total cost (as little as 13%), emission reductions of up to 92%, on average, can be achieved when using the greenest delivery strategy of drones and e-bikes. The other delivery options have varying tradeoffs between costs and environmental impact. The percentage of self-pickup customers is an influencing factor to consider when choosing the delivery strategy that best meets the organization’s budget and environmental goals, especially when using e-bikes in the second echelon.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Transport engineering", "Aeronautics", "Business", "Sustainable transport", "Engineering", "Sustainability", "Geography" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/15568318.2024.2419378" }, { "id": "https://openalex.org/W4210594127", "doi": "10.3390/drones6020039", "title": "Drones in B5G/6G Networks as Flying Base Stations", "year": 2022, "publication_date": "2022-02-05", "type": "article", "language": "en", "authors": [ "George Amponis", "Θωμάς Λάγκας", "Maria Zevgara", "Georgios P. Katsikas", "Thanos Xirofotos", "Ioannis D. Moscholios", "Panagiotis G. Sarigiannidis" ], "first_author": "George Amponis", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Advances in the fields of networking, broadband communications and demand for high-fidelity low-latency last-mile communications have rendered as-efficient-as-possible relaying methods more necessary than ever. This paper investigates the possibility of the utilization of cellular-enabled drones as aerial base stations in next-generation cellular networks. Flying ad hoc networks (FANETs) acting as clusters of deployable relays for the on-demand extension of broadband connectivity constitute a promising scenario in the domain of next-generation high-availability communications. Matters of mobility, handover efficiency, energy availability, optimal positioning and node localization as well as respective multi-objective optimizations are discussed in detail, with their core ideas defining the structure of the work at hand. This paper examines improvements to the existing cellular network core to support novel use-cases and lower the operation costs of diverse ad hoc deployments.", "keywords": [ "Drone", "Computer network", "Base station", "Computer science", "Wireless ad hoc network", "Cellular network", "Handover", "Broadband", "Relay", "Fidelity", "Core network", "Telecommunications" ], "cited_by_count": 94, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/6/2/39/pdf?version=1644401245" }, { "id": "https://openalex.org/W2883417042", "doi": "10.1002/net.21846", "title": "An iterative two‐step heuristic for the parallel drone scheduling traveling salesman problem", "year": 2018, "publication_date": "2018-07-27", "type": "article", "language": "en", "authors": [ "Raïssa G. Mbiadou Saleu", "Laurent Deroussi", "Dominique Feillet", "Nathalie Grangeon", "Alain Quilliot" ], "first_author": "Raïssa G. Mbiadou Saleu", "venue": "Networks", "publisher": "Wiley", "abstract": "A recent evolution in urban logistics involves the usage of drones. In this article, we address a heuristic solution of the parallel drone scheduling traveling salesman problem, recently introduced by Murray and Chu. In this problem, deliveries are split between a vehicle and drones. The vehicle performs a classical delivery tour, while the drones are constrained to perform back and forth trips. The objective is to minimize completion time. We propose an iterative two‐step heuristic, composed of: a coding step that transforms a solution into a customer sequence, and a decoding step that decomposes the customer sequence into a tour for the vehicle and trips for the drones. Decoding is expressed as a bicriteria shortest path problem and is carried out by dynamic programming. Experiments conducted on benchmark instances confirm the efficiency of the approach and give some insights on this drone delivery system.", "keywords": [ "Drone", "Travelling salesman problem", "Computer science", "Mathematical optimization", "Scheduling (production processes)", "Heuristic", "Shortest path problem", "TRIPS architecture", "Job shop scheduling", "Traveling purchaser problem", "Benchmark (surveying)", "2-opt" ], "cited_by_count": 119, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/net.21846" }, { "id": "https://openalex.org/W2947616598", "doi": "10.1109/access.2019.2919332", "title": "Convolutional Neural Network-Based Real-Time Object Detection and Tracking for Parrot AR Drone 2", "year": 2019, "publication_date": "2019-01-01", "type": "article", "language": "en", "authors": [ "Ali Rohan", "Mohammed Amin Rabah", "Sung-Ho Kim" ], "first_author": "Ali Rohan", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Recent advancements in the field of Artificial Intelligence (AI) have provided an opportunity to create autonomous devices, robots, and machines characterized particularly with the ability to make decisions and perform tasks without human mediation. One of these devices, Unmanned Aerial Vehicles (UAVs) or drones are widely used to perform tasks like surveillance, search and rescue, object detection and target tracking, parcel delivery (recently started by Amazon), and many more. The sensitivity in performing said tasks demands that drones must be efficient and reliable. For this, in this paper, an approach to detect and track the target object, moving or still, for a drone is presented. The Parrot AR Drone 2 is used for this application. Convolutional Neural Network (CNN) is used for object detection and target tracking. The object detection results show that CNN detects and classifies object with a high level of accuracy (98%). For real-time tracking, the tracking algorithm responds faster than conventionally used approaches, efficiently tracking the detected object without losing it from sight. The calculations based on several iterations exhibit that the efficiency achieved for target tracking is 96.5%.", "keywords": [ "Drone", "Computer science", "Artificial intelligence", "Convolutional neural network", "Object detection", "Computer vision", "Video tracking", "Tracking (education)", "Object (grammar)", "Deep learning", "Pattern recognition (psychology)" ], "cited_by_count": 129, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723347.pdf" }, { "id": "https://openalex.org/W4398776737", "doi": "10.1007/s10479-024-06019-z", "title": "Vehicle routing with multiple UAVs for the last-mile logistics distribution problem: hybrid distributed optimization", "year": 2024, "publication_date": "2024-05-24", "type": "article", "language": "en", "authors": [ "Abdeljawed Sadok", "Jalel Euchi", "Patrick Siarry" ], "first_author": "Abdeljawed Sadok", "venue": "Annals of Operations Research", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Vehicle routing problem", "Last mile (transportation)", "Mile", "Computer science", "Routing (electronic design automation)", "City logistics", "Distribution (mathematics)", "Transport engineering", "Computer network", "Engineering", "Geography", "Mathematics" ], "cited_by_count": 21, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10479-024-06019-z" }, { "id": "https://openalex.org/W4403826958", "doi": "10.1109/tnsm.2024.3487357", "title": "Holistic Service Provisioning in a UAV-UGV Integrated Network for Last-Mile Delivery", "year": 2024, "publication_date": "2024-10-28", "type": "article", "language": "en", "authors": [ "Xu Jia", "Xiao Liu", "Jiong Jin", "Wuzhen Pan", "Xuejun Li", "Yun Jin Yang" ], "first_author": "Xu Jia", "venue": "IEEE Transactions on Network and Service Management", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Effective last-mile delivery is pivotal in smart logistics system. While existing delivery network architectures, such as Drone-as-a-Service (DaaS), are capable of enhancing order delivery effectiveness, they often fall short in provisioning diverse delivery services. Furthermore, DaaS-based last-mile delivery systems face challenges from limited payload capacity and range. In this paper, we propose a UAV-UGV integrated network architecture based on Multi-access Edge Computing (MEC), denoted as DaaS+, encompassing the diverse delivery services from both Unmanned Aerial Vehicle (UAV) and Unmanned Ground Vehicle (UGV) for last-mile delivery. To optimize the effectiveness in the delivery process, the intricate overhead and constraints of heterogeneous delivery services are taken into the full consideration. Specifically, we present an energy-aware service model for the UAV-UGV integrated network that considers the deadline constraints of services. Additionally, we address issues of service unavailability during service provisioning. To identify optimal service provisioning plans, we design a novel Energy-Aware Holistic Service Provisioning Mechanism based on Particle Swarm Optimization (ES-PSO), which minimizes delivery energy consumption while adhering to service deadline constraints. Experimental results substantiate the effectiveness of our proposed solution, demonstrating its ability to generate superior service provisioning plans and significantly reduce total delivery energy consumption.", "keywords": [ "Computer science", "Provisioning", "Mile", "Last mile (transportation)", "Computer network", "Service (business)", "Embedded system" ], "cited_by_count": 19, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tnsm.2024.3487357" }, { "id": "https://openalex.org/W4390750412", "doi": "10.3390/app14020616", "title": "A New Last Mile Delivery Approach for the Hybrid Truck Multi-Drone Problem Using a Genetic Algorithm", "year": 2024, "publication_date": "2024-01-11", "type": "article", "language": "en", "authors": [ "Ebru Karaköse" ], "first_author": "Ebru Karaköse", "venue": "Applied Sciences", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "In this study, the use of drones in transportation and some optimization studies carried out in the literature so far were examined. Based on these investigations, a genetic algorithm-based method has been proposed to solve the hybrid truck multi-drone problem. With the proposed algorithm, scenarios have been created using single or multiple drones and one truck for a certain number of customers to be delivered, and results have been obtained. In these scenarios, the main aim is to minimize delivery time. The results obtained have also been compared with other optimization algorithms and other results in the literature, and in addition, it has been proven that there is an inverse relationship between the number of drones and the delivery time. As a result of the comparisons, it has been clearly seen that the proposed algorithm is quite successful in finding the most suitable route in the shortest time compared to other studies. A solution has been created for a real-world problem with the proposed genetic algorithm-based algorithm, and it has been concluded that it is quite successful here as well.", "keywords": [ "Drone", "Genetic algorithm", "Computer science", "Truck", "Mathematical optimization", "Algorithm", "Engineering", "Mathematics", "Machine learning", "Automotive engineering" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2076-3417/14/2/616/pdf?version=1704970493" }, { "id": "https://openalex.org/W3131709352", "doi": "10.1049/cim2.12006", "title": "RETRACTED: A viability study using conceptual models for last mile drone logistics operations in populated urban cities of India", "year": 2021, "publication_date": "2021-02-16", "type": "article", "language": "en", "authors": [ "Parth Rameshbhai Gabani", "Umang Bipin Gala", "Vaibhav S. Narwane", "Rakesh Dulichand Raut", "Usharani Hareesh Govindarajan", "Balkrishna Eknath Narkhede" ], "first_author": "Parth Rameshbhai Gabani", "venue": "IET Collaborative Intelligent Manufacturing", "publisher": "Institution of Engineering and Technology", "abstract": "Abstract Emerging Unmanned Aerial Vehicle (UAV) technologies have been under spotlight worldwide due to a promising spectrum of applications. Despite interesting use‐cases receiving worldwide media attention, drones are expected to have their most significant impact on supply chain and logistics systems in highly populated urban cities once the regulations for commercial purposes are lifted. This article proposes two models of drone‐delivery technology that can serve as a potential replacement in the Indian truck‐delivery system. First, a drone–truck hybrid delivery model is proposed with trucks carrying multiple drones. Second, a stand‐alone drone‐delivery model is proposed with separate charging infrastructural facilities at specific points. The two proposed models' findings present the advantages of significantly reducing carbon emissions, delivery costs, and time compared to truck‐based delivery. The hybrid drone–truck model eliminates the need for separate charging facilities saving initial infrastructural costs. In contrast, the stand‐alone drone model utilizes the current warehouse location facilities with charging stations on specific points for ease of adoption. This research presents initial viability suggesting that the drone technology can solve the current operational challenges in India's urban cities. Furthermore, vital factors are discussed to enable stakeholders to select a model for drone logistics systems planning and experimentations.", "keywords": [ "Drone", "Truck", "Last mile (transportation)", "Transport engineering", "Supply chain", "Business", "Computer science", "City logistics", "Mile", "Engineering", "Geography", "Marketing" ], "cited_by_count": 17, "is_retracted": true, "is_paratext": false, "open_access_url": "https://doi.org/10.1049/cim2.12006" }, { "id": "https://openalex.org/W4387948202", "doi": "10.17233/sosyoekonomi.2023.04.05", "title": "The Use of New Technologies in Logistics: Drone (UAV) Use in Last Mile Delivery", "year": 2023, "publication_date": "2023-10-26", "type": "article", "language": "en", "authors": [ "Yavuz Toraman", "Tuncel Öz" ], "first_author": "Yavuz Toraman", "venue": "Sosyoekonomi", "publisher": null, "abstract": "The increasing volume of e-commerce has complicated delivery operations, making it imperative to diversify the processes. Industry leaders have attempted to use drones, autonomous vehicles, electric vehicles, etc., in delivery processes. The research examined the adoption of consumer drone usage in delivery. The Technology Acceptance Model (TAM) was used in the study. In the analysis method, Partial Least Squares-Structural Equation Modelling (PLS-SEM), which is commonly used in the literature for multiple relationships due to the presence of multiple dependent and mediating variables, was used with the Smart PLS software package. Only the H5 hypothesis was rejected in the research, and the other hypotheses were accepted. When examining the hypothesis results, it was concluded that people are open to technological innovations and have a positive outlook on using drones in future product delivery processes.", "keywords": [ "Drone", "Structural equation modeling", "Partial least squares regression", "Last mile (transportation)", "Computer science", "Mile", "Business", "Marketing", "Machine learning", "Geography" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dergipark.org.tr/en/download/article-file/2862248" }, { "id": "https://openalex.org/W4224309848", "doi": "10.1007/s40305-021-00383-4", "title": "A Survey of Truck–Drone Routing Problem: Literature Review and Research Prospects", "year": 2022, "publication_date": "2022-04-06", "type": "article", "language": "en", "authors": [ "Yijing Liang", "Zhixing Luo" ], "first_author": "Yijing Liang", "venue": "Journal of the Operations Research Society of China", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Truck", "Vehicle routing problem", "Travelling salesman problem", "Routing (electronic design automation)", "Computer science", "Operations research", "Transport engineering", "Engineering", "Computer network" ], "cited_by_count": 90, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s40305-021-00383-4" }, { "id": "https://openalex.org/W4206447484", "doi": "10.4135/9781529780451", "title": "Last-Mile Drone Delivery: Is Wing's Business Model Sustainable?", "year": 2022, "publication_date": "2022-01-01", "type": "reference-entry", "language": "en", "authors": [ "Jashim Uddin Ahmed", "Quazi Tafsirul Islam", "Samsul Islam", "Asma Ahmed", "Kazi Pushpita Mim" ], "first_author": "Jashim Uddin Ahmed", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Business", "Aeronautics", "Wing", "Computer science", "Engineering", "Geography", "Aerospace engineering", "Biology" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.4135/9781529780451" }, { "id": "https://openalex.org/W3126630096", "doi": "10.1121/10.0003432", "title": "Psychoacoustic analysis of contra-rotating propeller noise for unmanned aerial vehicles", "year": 2021, "publication_date": "2021-02-01", "type": "article", "language": "en", "authors": [ "Antonio J. Torija", "Chaitanya C. Paruchuri", "Zhengguang Li" ], "first_author": "Antonio J. Torija", "venue": "The Journal of the Acoustical Society of America", "publisher": "Acoustical Society of America", "abstract": "Unmanned aerial vehicle (UAV) technologies are rapidly advancing due to the unlimited number of applications from parcel delivery to people transportation. As the UAV market expands, community noise impact will become a significant problem for public acceptance. Compact drone architectures based on contra-rotating propellers bring significant benefits in terms of aerodynamic performance and redundancy to ensure vehicle control in case of component failure. However, contra-rotating propellers are severely noisy if not designed appropriately. In the framework of a perception-influenced design approach, this paper investigates the optimal rotor spacing distance configuration to minimise noise annoyance. On the basis of a series of psychoacoustic metrics (i.e., loudness, fluctuation strength, roughness, sharpness, and tonality) and psychoacoustic annoyance (PA) models, the optimal rotor axial separation distance (expressed as a function of propeller blade diameter) is at a range from 0.2 to 0.4. This paper also discusses the performance of currently available psychoacoustic models to predict propeller noise annoyance and defines further work to develop a PA model optimised for rotating systems.", "keywords": [ "Psychoacoustics", "Annoyance", "Loudness", "Noise (video)", "Propeller", "Redundancy (engineering)", "Rotor (electric)", "Acoustics", "Aerodynamics", "Computer science", "Engineering", "Aerospace engineering" ], "cited_by_count": 56, "is_retracted": false, "is_paratext": false, "open_access_url": "http://usir.salford.ac.uk/id/eprint/59328/1/Manuscript.pdf" }, { "id": "https://openalex.org/W4295592551", "doi": "10.3390/drones6090249", "title": "Impact of the Integration of First-Mile and Last-Mile Drone-Based Operations from Trucks on Energy Efficiency and the Environment", "year": 2022, "publication_date": "2022-09-11", "type": "article", "language": "en", "authors": [ "Tamás Bányai" ], "first_author": "Tamás Bányai", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Supply chain solutions are based on first-mile and last-mile deliveries; their efficiency significantly influences the total cost of operation. Drone technologies make it possible to improve first-mile and last-mile operations, but the design and optimization of these solutions offers new challenges. Within the frame of this article, the author focuses on the impact of integrated first-mile/last-mile drone-based delivery services from trucks, analyzing the impact of solutions on energy efficiency, the environmental impact and sustainability. The author describes a novel model of drone-based integrated first-mile/last-mile services which makes it possible to analyze the impact of different typical solutions on sustainability. As the numerical examples and computational results show, the integrated first-mile-last-mile drone-based service from trucks could lead to a significant reduction in energy consumption and a reduction in virtual greenhouse gas (GHG) emissions, which would lead to a more sustainable logistics system. The numerical analysis of the scenarios shows that the increased application of drones and the integration of first-mile and last-mile delivery operations could decrease energy consumption by about 87%. This reduction in energy consumption, depending on the generation source of electricity, significantly increases the reduction in greenhouse gas emission.", "keywords": [ "Mile", "Last mile (transportation)", "Truck", "Drone", "Energy consumption", "Greenhouse gas", "Engineering", "Environmental science", "Transport engineering", "Computer science", "Automotive engineering", "Geography" ], "cited_by_count": 19, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/6/9/249/pdf?version=1663315895" }, { "id": "https://openalex.org/W3111422325", "doi": "10.1016/j.cor.2020.105170", "title": "The traveling salesman problem with release dates and drone resupply", "year": 2020, "publication_date": "2020-12-16", "type": "article", "language": "en", "authors": [ "Juan C. Pina-Pardo", "Daniel F. Silva", "Alice E. Smith" ], "first_author": "Juan C. Pina-Pardo", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Travelling salesman problem", "Drone", "Computer science", "Operations research", "Traveling purchaser problem", "Mathematical optimization", "2-opt", "Mathematics", "Algorithm", "Biology", "Botany" ], "cited_by_count": 82, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cor.2020.105170" }, { "id": "https://openalex.org/W4381487038", "doi": "10.1016/j.cor.2023.106319", "title": "A variable neighborhood search for parcel delivery by vehicle with drone cycles", "year": 2023, "publication_date": "2023-06-21", "type": "article", "language": "en", "authors": [ "Amro M. El-Adle", "Ahmed Eisa Ghoniem", "Mohamed Haouari" ], "first_author": "Amro M. El-Adle", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Benchmark (surveying)", "Travelling salesman problem", "Heuristic", "Variable neighborhood search", "Operations research", "Rendezvous", "Variable (mathematics)", "Key (lock)", "Metaheuristic", "Artificial intelligence" ], "cited_by_count": 27, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S0305054823001831" }, { "id": "https://openalex.org/W4399627602", "doi": "10.1016/j.jatrs.2024.100025", "title": "Coordinated last-mile deliveries with trucks and drones: A comparative study of operational modes", "year": 2024, "publication_date": "2024-06-13", "type": "article", "language": "en", "authors": [ "Yida Ding", "Jiaqi Wan", "Lin Qi Wei", "Kai Wang" ], "first_author": "Yida Ding", "venue": "Journal of the Air Transport Research Society", "publisher": null, "abstract": "Throughout the recent decade, drone delivery technology has been developed to address problems such as last-mile delivery and recurrent traffic jams in metropolitan regions. To resolve the relatively short travel range and limited capacity issues of drones, researchers have proposed to further enhance the utility of drones by deploying them with ground vehicles (e.g., trucks) in tandem. This new concept leads to a new transportation planning problem, i.e., coordinated delivery of trucks and drones (CDTD). In this paper, we conduct a comparative study of three representative operational models: the flying sidekick traveling salesman problem (FSTSP), the traveling salesman problem with drone (TSP-D), and the parallel drone scheduling traveling salesman problem (PDSTSP). Metrics including delivery efficiency and vehicle utilization rate are evaluated for the three models under various scenarios, to extract insights on which operational model is advantageous for which scenario. We also benchmark the algorithms for CDTD by various metrics including result quality, runtime and scalability, and conduct sensitivity analysis to assess the performance of the system under various system parameters, including drone speed, drone range and customer geographic distribution. Finally, a case study is conducted to demonstrate the superior performance of CDTD model as compared to classical TSP model based on real-world data. Experimental results demonstrate that the FSTSP and TSP-D highlight superior performance over PDSTSP and truck-only TSP when the majority of customers are out of the flight range of drone and the customer demand is clustered, as a result of the synchronization and compensation for limitations between the two types of vehicles.", "keywords": [ "Drone", "Travelling salesman problem", "Truck", "Computer science", "Scalability", "Operations research", "Range (aeronautics)", "Transport engineering", "Real-time computing", "Engineering", "Aerospace engineering" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.jatrs.2024.100025" }, { "id": "https://openalex.org/W4391731205", "doi": "10.1016/j.cities.2024.104867", "title": "Consumer acceptance of urban drone delivery: The role of perceived anthropomorphic characteristics", "year": 2024, "publication_date": "2024-02-10", "type": "article", "language": "en", "authors": [ "Xue Li", "Glenys Jia Xuan Lee", "Kum Fai Yuen" ], "first_author": "Xue Li", "venue": "Cities", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Business", "Advertising", "Marketing", "Internet privacy", "Computer science" ], "cited_by_count": 28, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cities.2024.104867" }, { "id": "https://openalex.org/W4401011187", "doi": "10.1007/s10479-024-06164-5", "title": "Optimizing last-mile delivery services: a robust truck-drone cooperation model and hybrid metaheuristic algorithm", "year": 2024, "publication_date": "2024-07-26", "type": "article", "language": "en", "authors": [ "Seyed Mohammad Javad Mirzapour Al-e-Hashem", "Taha‐Hossein Hejazi", "Ghazal Haghverdizadeh", "Mohsen Shidpour" ], "first_author": "Seyed Mohammad Javad Mirzapour Al-e-Hashem", "venue": "Annals of Operations Research", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Truck", "Computer science", "Metaheuristic", "Genetic algorithm", "Last mile (transportation)", "Theory of computation", "Hybrid algorithm (constraint satisfaction)", "Service (business)", "Vehicle routing problem", "Operations research", "Mathematical optimization" ], "cited_by_count": 16, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10479-024-06164-5" }, { "id": "https://openalex.org/W4287219751", "doi": "10.3390/su14158976", "title": "Mode Choice Modeling for Sustainable Last-Mile Delivery: The Greek Perspective", "year": 2022, "publication_date": "2022-07-22", "type": "article", "language": "en", "authors": [ "Amalia Polydoropoulou", "Athena Tsirimpa", "Ioannis D. Karakikes", "Ioannis Tsouros", "Ioanna Pagoni" ], "first_author": "Amalia Polydoropoulou", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "As the private sector is under heavy pressure to serve the ever-growing e-commerce market, the potential of implementing new disruptive mobility/logistics services for increasing the level of the current last-mile delivery (LMD) services, is emerging. Vehicle automation technology, characterized by high-capacity utilization and asset intensity, appears to be a prominent response to easing this pressure, while contributing to mitigation of the adverse effects associated with the deployment of LMD activities. This research studied the perceptions of Greek end-users/consumers, regarding the introduction of autonomous/automated/driverless vehicles (AVs) in innovative delivery services. To achieve this, a mixed logit model was developed, based on a Stated Preferences (SP) experiment, designed to capture the demand of alternative last-mile delivery modes/services, such as drones, pods, and autonomous vans, compared to traditional delivery services. The results show that the traditional delivery, i.e., having a dedicated delivery person who picks up the parcels at a consolidation point and delivers them directly to the recipients while driving a non-autonomous vehicle—conventional van, bike, e-bike, e-scooter—remains the most acceptable delivery method. Moreover, the analysis indicated that there is no interest yet in deploying home deliveries with drones or AVs, and that participants are unwilling to pay extra charges for having access to more advanced last-mile delivery modes/services. Thus, it is important to promote the benefits of innovative modes and services for LMD, in order to increase public awareness and receptivity in Greece.", "keywords": [ "Last mile (transportation)", "Business", "Service delivery framework", "Mile", "Software deployment", "Mixed logit", "Transport engineering", "Service (business)", "Environmental economics", "Marketing", "Engineering", "Computer science" ], "cited_by_count": 26, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/14/15/8976/pdf?version=1658475846" }, { "id": "https://openalex.org/W4389934305", "doi": "10.1109/tevc.2023.3344350", "title": "Locating Drone Stations for a Truck-Drone Delivery System in Continuous Space", "year": 2023, "publication_date": "2023-12-19", "type": "article", "language": "en", "authors": [ "Lingyun Zhou", "Daniel F. Silva", "Alice E. Smith" ], "first_author": "Lingyun Zhou", "venue": "IEEE Transactions on Evolutionary Computation", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Truck-drone delivery systems have been proposed for sustainable and economical last-mile distribution, especially in urban environments. To widen the service range, some works have recommended adding facilities such as drone stations, considering the problem in discrete space by choosing from a pre-defined set. In this paper, an evolutionary optimization approach to the design decision of where to locate drone stations in the continuous plane is introduced, modeled, and solved. Drone stations serve as facilities for storage, charging, and launching. A truck (or other land transport means) transports parcels to the drone stations from a depot and the drones launch from the stations and deliver the parcels to each customer. The objective is to determine the positions of the drone stations in two-dimensional space and establish the shortest fixed truck route from the depot through all the stations and returning to the depot. The problem is constrained by the radius of service for each drone and all customers must be served, if possible. We formulate the problem as a constrained nonlinear optimization problem and present two versions of an algorithm using particle swarm optimization with a subordinate dynamic program. Computational results show that our approach achieves much better results than a standard commercial nonlinear solver in a similar amount of computational time for both maximizing coverage of customers and minimizing distance of the truck delivery route. A design case study concerning healthcare delivery throughout the Birmingham, Alabama (USA) metropolitan area is provided.", "keywords": [ "Drone", "Truck", "Computer science", "Particle swarm optimization", "Last mile (transportation)", "Solver", "Metropolitan area", "Travelling salesman problem", "Operations research", "Real-time computing", "Transport engineering", "Engineering" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tevc.2023.3344350" }, { "id": "https://openalex.org/W4386310557", "doi": "10.2139/ssrn.4557554", "title": "Last Mile Delivery with Drones and Sharing Economy", "year": 2023, "publication_date": "2023-01-01", "type": "preprint", "language": "en", "authors": [ "Mehdi Behroozi", "Dinghao Ma" ], "first_author": "Mehdi Behroozi", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Sharing economy", "Business", "Computer science", "Geography", "World Wide Web" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4557554" }, { "id": "https://openalex.org/W4409385083", "doi": "10.1016/j.geits.2025.100310", "title": "A comparative review of user acceptance factors for drones and sidewalk robots in autonomous last mile delivery", "year": 2025, "publication_date": "2025-04-12", "type": "article", "language": "en", "authors": [ "Didem Cicek", "Burak Kantarcı", "S. Schillo" ], "first_author": "Didem Cicek", "venue": "Green Energy and Intelligent Transportation", "publisher": "Elsevier BV", "abstract": "Autonomous delivery technologies play a pivotal role in meeting the high expectations of customers while addressing the sustainability challenges posed by last-mile delivery traffic, particularly in urban areas. Over the past five years, research on user acceptance of these groundbreaking technologies has surged. This paper represents the first comprehensive review that consolidates and compares user acceptance factors related to deliveries by drones and sidewalk robots, drawing from global questionnaire-based studies. Our research reveals some common factors that consistently influence user acceptance for both drone and sidewalk robot deliveries and also sheds light on technology-specific acceptance factors. However, it's important to recognize that some of these factors may vary depending on the demographics and location of the studies conducted. Our findings intend to provide managerial insights to technology and policy makers, enabling strategic planning for the adoption of these innovative technologies. • First comprehensive review comparing user acceptance of drone and robot deliveries based on studies from the past five years. • Identifying common factors that consistently influence user acceptance for both drone and sidewalk robot deliveries. • Presenting opportunities to reduce environmental impact and improve cost efficiency in the delivery sector. • Discussing mainstream user acceptance theories, which guide the empirical studies on user acceptance of autonomous last mile delivery. • Managerial insights for technology developers and policymakers to aid in strategic planning for the adoption of autonomous delivery technologies.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Robot", "Computer science", "Engineering", "Aeronautics", "Human–computer interaction", "Transport engineering", "Geography", "Artificial intelligence" ], "cited_by_count": 14, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.geits.2025.100310" }, { "id": "https://openalex.org/W4403981910", "doi": "10.1016/j.trip.2024.101253", "title": "Drones for automated parcel delivery: Use case identification and derivation of technical requirements", "year": 2024, "publication_date": "2024-11-01", "type": "article", "language": "en", "authors": [ "Simon Zieher", "Ertug Olcay", "Klaus Kefferpütz", "Babak Salamat", "Sebastian-Sven Olzem", "Gerhard Elsbacher", "Henri Meeß" ], "first_author": "Simon Zieher", "venue": "Transportation Research Interdisciplinary Perspectives", "publisher": "Elsevier BV", "abstract": "Drone-based parcel delivery is a rapidly growing domain posing many technological and operational challenges. Drone technologies have been under increasing levels of investigation and development over the past years. Since the realization of drone-based delivery can only be economically feasible at large scales, it requires processes that address the outstanding challenges holistically. However, the majority of research focuses on individual aspects such as environmental perception, route planning, operational design, and business models without addressing the challenges in the overall system. This paper conducts a quantitative analysis of the requirements for identified use cases that are considered relevant for the upcoming future. We provide a comprehensive technology overview and derive requirements and specifications for the targeted use cases that are not fulfilled by the current state-of-the-art. The use cases are not only related to last-mile delivery but also long-distance (hub-to-hub) logistics as well as courier and express delivery.", "keywords": [ "Identification (biology)", "Drone", "Computer science", "Engineering", "Systems engineering", "Software engineering" ], "cited_by_count": 26, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trip.2024.101253" }, { "id": "https://openalex.org/W4404262463", "doi": "10.3390/smartcities7060134", "title": "Drone-Assisted Last-Mile Delivery Under Windy Conditions: Zero Pollution Solutions", "year": 2024, "publication_date": "2024-11-10", "type": "article", "language": "en", "authors": [ "Özlem Gürel", "Şeyda Serdarasan" ], "first_author": "Özlem Gürel", "venue": "Smart Cities", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "As cities expand and the global push for zero pollution intensifies, sustainable last-mile delivery (LMD) systems are essential to minimizing environmental and health impacts. This study addresses the need for more sustainable LMD by examining the integration of wind conditions into drone-assisted deliveries, focusing on their effects on air and noise pollution in urban areas. We extend the flying sidekick traveling salesman problem (FSTSP) by incorporating meteorological factors, specifically wind, to assess drone delivery efficiency in varying conditions. Our results show that while drones significantly reduce greenhouse gas emissions compared to traditional delivery vehicles, their contribution to noise pollution remains a concern. This research highlights the environmental advantages of using drones, particularly in reducing CO2 emissions, while also emphasizing the need for further investigation into mitigating their noise impact. By evaluating the trade-offs between air and noise pollution, this study provides insights into developing more sustainable, health-conscious delivery models that contribute to smart city initiatives. The findings inform policy, urban planning, and logistics strategies aimed at achieving zero pollution goals and improving urban livability.", "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Environmental science", "Zero (linguistics)", "Meteorology", "Pollution", "Aeronautics", "Computer science", "Engineering", "Geography", "Geodesy" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2624-6511/7/6/134/pdf?version=1731241425" }, { "id": "https://openalex.org/W4281672706", "doi": "10.1080/24725854.2022.2060535", "title": "Branch-price-and-cut for trucks and drones cooperative delivery", "year": 2022, "publication_date": "2022-05-13", "type": "article", "language": "en", "authors": [ "Lu Zhen", "Jiajing Gao", "Zheyi Tan", "Shuaian Wang", "Roberto Baldacci" ], "first_author": "Lu Zhen", "venue": "IISE Transactions", "publisher": "Taylor & Francis", "abstract": "The truck and drone-based cooperative model of delivery can improve the efficiency of last mile delivery, and has thus increasingly attracted attention in academia and from practitioners. In this study, we examine a vehicle routing problem and apply a cooperative form of delivery involving trucks and drones. We propose a mixed-integer programming model and a branch-price-and-cut-based exact algorithm to address this problem. To reduce the computation time, we design several acceleration strategies, including a combination of dynamic programming and calculus-based approximation for the pricing problem, and various effective inequalities for the restricted master problem. Numerical experiments are conducted to validate the effectiveness and efficiency of the proposed solution.", "keywords": [ "Truck", "Drone", "Computer science", "Aeronautics", "Business", "Automotive engineering", "Engineering", "Biology" ], "cited_by_count": 78, "is_retracted": false, "is_paratext": false, "open_access_url": "http://ira.lib.polyu.edu.hk/bitstream/10397/99079/1/trucks%20and%20drones.pdf" }, { "id": "https://openalex.org/W3124145329", "doi": "10.2139/ssrn.3338436", "title": "The Multiple Flying Sidekicks Traveling Salesman Problem: Parcel Delivery with Multiple Drones", "year": 2019, "publication_date": "2019-01-01", "type": "preprint", "language": "en", "authors": [ "Chase C. Murray", "Ritwik Raj" ], "first_author": "Chase C. Murray", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Travelling salesman problem", "Drone", "Computer science", "Aeronautics", "Operations research", "Engineering", "Biology", "Algorithm" ], "cited_by_count": 21, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.3338436" }, { "id": "https://openalex.org/W4363675726", "doi": "10.1016/j.techsoc.2023.102250", "title": "Upcoming drone delivery services: A perceptions-based clustering of citizens in Lisbon", "year": 2023, "publication_date": "2023-04-10", "type": "article", "language": "en", "authors": [ "Anastasia Bafouni - Kotta", "Jonathan Villanueva", "Sofia Kalakou", "José G. Dias" ], "first_author": "Anastasia Bafouni - Kotta", "venue": "Technology in Society", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Metropolitan area", "Business", "Service (business)", "Service provider", "Service delivery framework", "Cluster analysis", "Marketing", "Public relations", "Political science", "Computer science", "Geography" ], "cited_by_count": 23, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/10071/28678" }, { "id": "https://openalex.org/W4401883333", "doi": "10.1080/23249935.2024.2392611", "title": "Joint optimization of truck-drone routing for last-mile deliveries in urban areas", "year": 2024, "publication_date": "2024-08-26", "type": "article", "language": "en", "authors": [ "Meiqi Liu", "Yalan Li", "Xinwei Wang" ], "first_author": "Meiqi Liu", "venue": "Transportmetrica A Transport Science", "publisher": "Taylor & Francis", "abstract": "This paper presents a joint routing optimization model to satisfy the on-demand customer requirements by minimising the transportation and time penalty costs of trucks and drones, considering the constraints on paths and delivery time of trucks and drones, the drone battery capacity limit, and the customer demands. The improved genetic algorithm is proposed to solve the optimization model followed by the computational experiments demonstrating the superiority of the improved genetic algorithm over the original genetic algorithm in computational efficiency, economy, and punctuality. Further, the comparative analysis demonstrates that the multi-drone joint delivery mode considering the customer demands performs better than the other delivery modes and that the delivery routes can be re-optimised promptly to satisfy the real-time customer demands. The sensitivity analysis on the drone design parameters provides theoretical insights into deploying the size and speed of drone platoons when promoting truck-drone joint delivery in applications.", "keywords": [ "Mile", "Drone", "Truck", "Last mile (transportation)", "Joint (building)", "Routing (electronic design automation)", "Vehicle routing problem", "Transport engineering", "Computer science", "Aeronautics", "Engineering", "Geography" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/23249935.2024.2392611" }, { "id": "https://openalex.org/W4407392406", "doi": "10.1016/j.cor.2025.107006", "title": "An exact method and a heuristic for last-mile delivery drones routing with centralized graph-based airspace control", "year": 2025, "publication_date": "2025-02-12", "type": "article", "language": "en", "authors": [ "Jorge Luiz Franco", "Vitor Curtis", "Edson Luiz França Senne", "Filipe Alves Neto Verri" ], "first_author": "Jorge Luiz Franco", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Mile", "Heuristic", "Routing (electronic design automation)", "Vehicle routing problem", "Graph", "Mathematical optimization", "Operations research", "Mathematics", "Computer network", "Artificial intelligence" ], "cited_by_count": 14, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cor.2025.107006" }, { "id": "https://openalex.org/W2742151358", "doi": "10.1109/icufn.2017.7993739", "title": "Enabling drone as a service: OneM2M-based UAV/drone management system", "year": 2017, "publication_date": "2017-07-01", "type": "conference-paper", "language": "en", "authors": [ "Sung-Chan Choi", "Nak-Myung Sung", "Jong-Hong Park", "Il-Yeop Ahn", "Jaeho Kim" ], "first_author": "Sung-Chan Choi", "venue": null, "publisher": null, "abstract": "Recently, commercial Unmanned Aerial Vehicles (UAVs) called drones have received a lot of interest in the public and civil environments for their possibility as a potential enabler of promising services such as traffic monitoring, ad hoc network establishment in a disaster area, parcel delivery, remote sensing and streaming on various service scenarios. However, in order to support those services smoothly, a stable and reliable UAV/drone control and management system is needed. Utilizing a standard-based communication scheme is helpful in realizing efficient control and management of UAV/drone-based operations. Regarding this issue, the oneM2M global standard, which provides machine-to-machine (M2M) and the Internet of Things (IoT) service layer for globally interoperable M2M/IoT solutions, has paramount benefit. In this paper, we present oneM2M global standard platform based UAV/drone management system based on the Interworking Proxy Entity (IPE) for drones. We also show our implementation and demonstration for the oneM2M based UAV/drone management system.", "keywords": [ "Drone", "Computer science", "Interoperability", "Service (business)", "Scheme (mathematics)", "Internet of Things", "Computer security", "Computer network", "World Wide Web" ], "cited_by_count": 25, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/icufn.2017.7993739" }, { "id": "https://openalex.org/W4289917419", "doi": "10.1016/j.patter.2022.100569", "title": "Drone flight data reveal energy and greenhouse gas emissions savings for very small package delivery", "year": 2022, "publication_date": "2022-08-01", "type": "article", "language": "en", "authors": [ "Thiago A. Rodrigues", "Jay Patrikar", "Natalia Lombardi Oliveira", "H. Scott Matthews", "Sebastian Scherer", "Constantine Samaras" ], "first_author": "Thiago A. Rodrigues", "venue": "Patterns", "publisher": "Elsevier BV", "abstract": "Uncrewed aerial vehicles (UAVs) for last-mile deliveries will affect the energy productivity of delivery and require new methods to understand energy consumption and greenhouse gas (GHG) emissions. We combine empirical testing of 188 quadcopter flights across a range of speeds with a first-principles analysis to develop a usable energy model and a machine-learning algorithm to assess energy across takeoff, cruise, and landing. Our model shows that an electric quadcopter drone with a very small package (0.5 kg) would consume approximately 0.08 MJ/km and result in 70 g of CO 2 e per package in the United States. We compare drone delivery with other vehicles and show that energy per package delivered by drones (0.33 MJ/package) can be up to 94% lower than conventional transportation modes, with only electric cargo bicycles providing lower GHGs/package. Our open model and coefficients can assist stakeholders in understanding and improving the sustainability of small package delivery.", "keywords": [ "Quadcopter", "Drone", "Greenhouse gas", "Takeoff", "Energy consumption", "Automotive engineering", "Environmental science", "Engineering", "Aerospace engineering", "Electrical engineering" ], "cited_by_count": 102, "is_retracted": false, "is_paratext": false, "open_access_url": "http://www.cell.com/article/S2666389922001805/pdf" }, { "id": "https://openalex.org/W4315489741", "doi": "10.1016/j.swevo.2023.101246", "title": "A GV-drone arc routing approach for urban traffic patrol by coordinating a ground vehicle and multiple drones", "year": 2023, "publication_date": "2023-01-10", "type": "article", "language": "en", "authors": [ "Binjie Xu", "Kexin Zhao", "Qizhang Luo", "Guohua Wu", "Witold Pedrycz" ], "first_author": "Binjie Xu", "venue": "Swarm and Evolutionary Computation", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Simulated annealing", "Patrolling", "Real-time computing", "Algorithm" ], "cited_by_count": 47, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.swevo.2023.101246" }, { "id": "https://openalex.org/W4390226701", "doi": "10.1016/j.cor.2023.106514", "title": "Parallel drone scheduling vehicle routing problems with collective drones", "year": 2023, "publication_date": "2023-12-26", "type": "article", "language": "en", "authors": [ "Roberto Montemanni", "Mauro Dell’Amico", "Andrea Corsini" ], "first_author": "Roberto Montemanni", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": "We study last-mile delivery problems where trucks and drones collaborate to deliver goods to final customers. In particular, we focus on problem settings where either a single truck or a fleet with several homogeneous trucks work in parallel to drones, and drones have the capability of collaborating for delivering missions. This cooperative behaviour of the drones, which are able to connect to each other and work together for some delivery tasks, enhance their potential, since connected drone has increased lifting capabilities and can fly at higher speed, overcoming the main limitations of the setting where the drones can only work independently. In this work, we contribute a Constraint Programming model and a valid inequality for the version of the problem with one truck, namely the Parallel Drone Scheduling Traveling Salesman Problem with Collective Drones and we introduce for the first time the variant with multiple trucks, called the Parallel Drone Scheduling Vehicle Routing Problem with Collective Drones. For the latter version of the problem, we propose two Constraint Programming models and a Mixed Integer Linear Programming model. An extensive experimental campaign leads to state-of-the-art results for the problem with one truck and some understanding of the presented models’ behaviour on the version with multiple trucks. Some insights about future research are finally discussed.", "keywords": [ "Drone", "Truck", "Travelling salesman problem", "Computer science", "Vehicle routing problem", "Scheduling (production processes)", "Integer programming", "Constraint programming", "Operations research", "Routing (electronic design automation)", "Mathematical optimization", "Computer network" ], "cited_by_count": 47, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cor.2023.106514" }, { "id": "https://openalex.org/W4408619551", "doi": "10.1016/j.trpro.2025.03.076", "title": "Last-Mile Delivery Optimization: Recent Approaches and Advances", "year": 2025, "publication_date": "2025-01-01", "type": "article", "language": "en", "authors": [ "Abdullahi Sani Shuaibu", "Ashraf Mahmoud", "Tarek Sheltami" ], "first_author": "Abdullahi Sani Shuaibu", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "There are numerous challenges in the last mile of urban logistics operations related to efficiency, resource allocation, environmental sustainability, and delivery operations. Technological innovation in recent years is trying to fill these loopholes and bring out efficient, reliable, and sustainable last-mile delivery. This paper provides a summary of the current optimization approaches in last-mile delivery, covering traditional Linear Programming methods, sophisticated algorithmic techniques known as metaheuristic methods, Artificial Intelligence (AI) based approaches, experience-based methodologies, and energy conservation techniques. These sets of optimization techniques—derived from optimization theory and computational algorithms—are diverse in their strategies for route planning, resource allocation, and energy management and tailored to the complex nature of urban delivery networks. In this regard, promising future technologies have also been discussed to re-orient last-mile delivery. Autonomous delivery by drones is one such game-changing solution that can enable rapid and eco-friendly delivery capabilities. Smart delivery acceptance systems through extensive use of advanced sensor technologies and data analytics help simplify parcel reception processes and make them much more efficient and safer. In the context of changing customer preferences and the emergence of e-commerce, the optimization of the last mile is critical in satisfying increasing demand while ensuring environmental sustainability and operational efficiency. Such innovative technologies and optimization strategies will enable delivery providers to better manage urban logistics challenges to deliver better customer experience and achieve sustainable growth in the last mile of delivery.", "keywords": [ "Mile", "Last mile (transportation)", "Computer science", "Engineering", "Geography" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trpro.2025.03.076" }, { "id": "https://openalex.org/W4404317033", "doi": "10.1109/tem.2024.3494051", "title": "Consumer Preferences and Barriers in the Adoption of Drone Delivery Services: A Comprehensive Analysis", "year": 2024, "publication_date": "2024-11-13", "type": "article", "language": "en", "authors": [ "Marina Dabić", "João J. Ferreira", "João Morais Lopes", "Sofia Gomes" ], "first_author": "Marina Dabić", "venue": "IEEE Transactions on Engineering Management", "publisher": "Institute of Electrical and Electronics Engineers", "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 1108 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", "Business", "Marketing", "Knowledge management", "Computer science" ], "cited_by_count": 26, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tem.2024.3494051" }, { "id": "https://openalex.org/W4321487121", "doi": "10.1016/j.ejor.2023.02.031", "title": "Planning robust drone-truck delivery routes under road traffic uncertainty", "year": 2023, "publication_date": "2023-02-22", "type": "article", "language": "en", "authors": [ "Yu Long Yang", "Chiwei Yan", "Yufeng Cao", "Roberto Roberti" ], "first_author": "Yu Long Yang", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Computer science", "Operations research", "Last mile (transportation)", "Profit (economics)", "Robust optimization", "Variance (accounting)", "Mathematical optimization", "Business", "Engineering", "Automotive engineering" ], "cited_by_count": 103, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ejor.2023.02.031" }, { "id": "https://openalex.org/W4295182934", "doi": "10.1080/01441647.2022.2119297", "title": "A review on the factors influencing the adoption of new mobility technologies and services: autonomous vehicle, drone, micromobility and mobility as a service", "year": 2022, "publication_date": "2022-09-08", "type": "article", "language": "en", "authors": [ "Yuerong Zhang", "Maria Kamargianni" ], "first_author": "Yuerong Zhang", "venue": "Transport Reviews", "publisher": "Taylor & Francis", "abstract": "New mobility technologies and services could address a series of transport-related problems such as pollution, congestion, unpleasant travel experiences, as well as first- and last-mile in-connectivity. Understanding the key factors influencing adoption and enablers is critical to the rollout of the new mobility technologies and services. The objective of this paper is to conduct a systematic review of the new mobility technologies and services, especially on autonomous vehicles, drones, micromobility and Mobility as a Service (MaaS). The ultimate goal is to gain a deeper insight into the factors that affect the adoption or preferences of these technologies and services and thus provide policy implications at the strategic level. The results of the review identified several (1) shared, (2) exclusive, (3) opposing and (4) mixed impacts factors that strongly influence the uptake of new mobilities. The synthesised finding will contribute to policy decisions, particularly regarding the sequencing of the launch and development priorities of new mobility technologies and services. To encourage the uptake of new mobility technologies and services, further promotion would benefit from (1) embedding a spatio-temporal perspective, (2) undertaking a careful market segmentation and (3) a careful segmentation of technology and services based on features, application contexts and purposes.", "keywords": [ "Drone", "Business", "Service (business)", "Emerging technologies", "Marketing", "Promotion (chess)", "Market segmentation", "Telecommunications", "Computer science" ], "cited_by_count": 135, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/01441647.2022.2119297" }, { "id": "https://openalex.org/W4206167952", "doi": "10.1007/978-3-030-92916-9_3", "title": "Last Mile Delivery by Drone: a Technoeconomic Approach", "year": 2021, "publication_date": "2021-01-01", "type": "conference-paper", "language": "en", "authors": [ "Evgenia Skoufi", "Evangelia Filiopoulou", "Angelos Skoufis", "Christos Michalakelis" ], "first_author": "Evgenia Skoufi", "venue": "Lecture notes in computer science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Last mile (transportation)", "Popularity", "Mile", "Computer science", "Distribution (mathematics)", "Supply chain", "Operations research", "Business", "Engineering", "Marketing" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-030-92916-9_3" }, { "id": "https://openalex.org/W4311598161", "doi": "10.3390/s22249858", "title": "Analysis of Modern vs. Conventional Development Technologies in Transportation—The Case Study of a Last-Mile Delivery Process", "year": 2022, "publication_date": "2022-12-15", "type": "article", "language": "en", "authors": [ "Mariusz Kostrzewski", "Yahya Abdelatty", "Ahmed Eliwa", "M. Nader" ], "first_author": "Mariusz Kostrzewski", "venue": "Sensors", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Transportation plays a significant role in the global economy and society and takes part in a lot of different processes such as mass transportation and the supply chain. Therefore, it is crucial to introduce modern technologies in this area of the economy in the context of Industry 4.0. The main scope of this study is to develop a model that supports analyzing last-mile logistics modern solutions using the latest technologies such as road autonomous delivery robots (RADRs), civil drones, or smart bikes, and compare them to conventional solutions (delivery vehicles). Multi-criteria decision analysis (MCDA) was applied to build a formal comparison model that scores the solutions and weights different criteria according to decision-makers and placeholders, to rank the solutions from the most crucial option to the weakest in a predetermined scenario with set parameters and conditions (three varied scenarios were included in the present investigation). The results of the model were in favor of using civil drones or smart bicycles to perform light deliveries in small urban areas (these key findings support the assumptions that are often manifested in speech in the context of the use of new technologies). The modern solutions scored almost 40-80% higher in total in the conglomeration of assessment criteria (such as safety, economy, laws and regulations, operation time for the delivery, environment, and payload) than the conventional solution, which indicates the importance of studying the implementation of such technologies. An interesting result of the study is the operational cost reduction by ca. 60-74% in favor of autonomous delivery robots, 89-93% in favor of civil delivery drones, and 87-90% in favor of smart bikes vs. conventional delivery trucks/vans. Yet, it should be underlined that the results may vary with different assumptions within the MCDA method.", "keywords": [ "Context (archaeology)", "Scope (computer science)", "Multiple-criteria decision analysis", "Payload (computing)", "Process (computing)", "Drone", "Computer science", "Last mile (transportation)", "Supply chain", "Emerging technologies", "Risk analysis (engineering)", "Transport engineering" ], "cited_by_count": 33, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1424-8220/22/24/9858/pdf?version=1671087119" }, { "id": "https://openalex.org/W2519215198", "doi": "10.1007/978-3-319-31132-6_5", "title": "Bikes or Drones to the Consumer: The Logistical Challenge of the Last Mile", "year": 2016, "publication_date": "2016-01-01", "type": "book-chapter", "language": "en", "authors": [ "Carlos Cordón", "Pau Garcia-Milà", "Teresa Ferreiro Vilarino", "Pablo Caballero" ], "first_author": "Carlos Cordón", "venue": "Management for professionals", "publisher": "Springer Nature", "abstract": null, "keywords": [ "Drone", "Big data", "Last mile (transportation)", "Mile", "Business", "Amazon rainforest", "Section (typography)", "Value (mathematics)", "Computer science", "Advertising", "Geography" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-319-31132-6_5" }, { "id": "https://openalex.org/W4319018095", "doi": "10.3390/su15032621", "title": "Public Acceptance of the Use of Drones in City Logistics: A Citizen-Centric Perspective", "year": 2023, "publication_date": "2023-02-01", "type": "article", "language": "en", "authors": [ "Sandra Melo", "Flávia Silva", "Mohammad Abbasi", "Parisa Ahani", "Joaquim Macedo" ], "first_author": "Sandra Melo", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The specific use of drones for city logistics has been increasingly studied and analysed by research and industry. An examination of the findings in the literature indicates that drones have proven to be a useful and added-value tool in the most diverse fields. However, the importance of the citizen’s perspective has still not been sufficiently incorporated into the deployment of urban air mobility systems. This paper seeks to contribute to a better understanding of the interaction between public knowledge and the awareness of, and engagement with, drones, alongside the concerns and support for their use in city logistics. A survey was carried out in Portugal of the citizens with a view to better understanding their attitude towards such a goal. The survey revealed a positive attitude towards the use of drones in city logistics and that socio-demographic characteristics, namely gender, education level, job occupation, age, and home location are not directly correlated with citizens’ attitudes. Moreover, citizens revealed that they favour a potential environmental benefit over a reduction in delivery time, which they would be willing to pay for. The policy implications derived can help develop the knowledge of public perception about drone usage for transport-related tasks.", "keywords": [ "Drone", "Perspective (graphical)", "Software deployment", "Business", "Marketing", "Value (mathematics)", "Perception", "Public relations", "Political science", "Psychology", "Engineering" ], "cited_by_count": 30, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/15/3/2621/pdf?version=1675993094" }, { "id": "https://openalex.org/W4293240185", "doi": "10.1177/03611981221086632", "title": "First and Last Miles by Cargo Bikes: Ecological Commitment or Economically Feasible? The Case of a Parcel Service Company in Paris", "year": 2022, "publication_date": "2022-04-28", "type": "article", "language": "en", "authors": [ "Antoine Robichet", "Patrick Niérat", "François Combes" ], "first_author": "Antoine Robichet", "venue": "Transportation Research Record Journal of the Transportation Research Board", "publisher": "SAGE Publishing", "abstract": "Urban logistics is a key step in distribution chains. It implies the use of trucks in congested areas, and generates numerous externalities (congestion, noise, pollution, etc.). Supply chain configurations and consumer behaviors are undergoing deep changes, with a significant increase in the intensity of urban logistics and a diversification of delivery channels within cities. This is an important challenge for city sustainability, as urban logistics is an essential economic activity, and yet the source of intense negative externalities. Numerous directions are currently being explored to rethink urban logistics, such as drones, cargo bikes, crowd logistics, and so forth. However, the economic and environmental relevance of these technologies is not yet perfectly clear. This paper focuses on the conditions for the financial sustainability of cargo bikes compared with electric light commercial vehicles (LCVs). The analysis is based on real data, provided by the parcel service company DB Schenker. The dataset consists of 600,000 operations made in Paris over two months. Operations with electric LCV are assumed to be identical to conventional LCV; the cost comparison is based on a total cost of ownership approach. Operations with cargo bikes assumes that eligible shipments are first brought to micro hubs within the city by electric LCV, then delivered by cargo bike. The numbers and locations of micro hubs are optimized. Results show that a cargo bike solution can be more cost-efficient than electric LCV with a few micro hubs located where the demand is densest, but they can only be relevant financially in those conditions.", "keywords": [ "Truck", "Service (business)", "Business", "Externality", "Sustainability", "Supply chain", "Transport engineering", "Diversification (marketing strategy)", "Industrial organization", "Environmental economics", "Marketing", "Economics" ], "cited_by_count": 32, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1177/03611981221086632" }, { "id": "https://openalex.org/W4399094864", "doi": "10.1177/03611981241248156", "title": "Literature Synthesis of Emerging Last-Mile Delivery Technologies and their Applications to Rural Areas: Drones, Autonomous Delivery Vehicles, and Truck-Drones", "year": 2024, "publication_date": "2024-05-28", "type": "article", "language": "en", "authors": [ "Marcella Kaplan", "Kevin P. Heaslip" ], "first_author": "Marcella Kaplan", "venue": "Transportation Research Record Journal of the Transportation Research Board", "publisher": "SAGE Publishing", "abstract": "Rural areas have the distinct opportunity to become trendsetters of innovation and technology, molding and optimizing delivery advances to operate in a way that meets their needs. Drones, autonomous delivery vehicles (ADVs), and truck-drones have the potential to improve rural delivery services significantly. However, rural environments have considerably different characteristics than urban or suburban areas. Therefore, delivery services must be evaluated specifically for the rural use case because the outcome of rural drone delivery is likely different from urban. This study conducted a systematic literature review about the current state-of-the-art drone, ADV, and truck-drone package delivery in rural areas (excluding medical or healthcare delivery). Drones can significantly reduce rural delivery emissions and costs while increasing efficiency. ADVs have the potential to greatly improve rural delivery efficiency. The truck-drone solution is one of the best mode choices for rural delivery because the truck can travel longer distances while the drone can cross challenging geography without delay. The literature review identified a general need for more drone, ADV, and truck-drone delivery research focusing on rural locations. There also is a need for research about the specific economic, environmental, and societal impacts of drone, ADV, and truck-drone delivery in rural areas. There is a significant gap in the literature on realistic rural delivery modeling and gaps about attitudes and perceptions of drone, ADV, and truck-drone delivery services in rural areas. With additional research, innovative delivery modes and technologies can become more cost-effective, accessible, and efficient in rural areas.", "keywords": [ "Drone", "Truck", "Last mile (transportation)", "Mile", "Transport engineering", "Engineering", "Aeronautics", "Business", "Automotive engineering", "Geography" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1177/03611981241248156" }, { "id": "https://openalex.org/W4403395536", "doi": "10.47941/ijscl.2286", "title": "Drone Integration in Last-Mile Delivery Operations", "year": 2024, "publication_date": "2024-10-13", "type": "article", "language": "en", "authors": [ "Ravindra Kumar Patro", "Subhash Chandra", "Janaki Prasad Patro" ], "first_author": "Ravindra Kumar Patro", "venue": "International Journal of Supply Chain and Logistics", "publisher": null, "abstract": "Purpose: This research examines the integration of drone technology into last-mile delivery operations, focusing on its impact on supply chain efficiency, cost reduction, and sustainability. The study explores operational challenges, such as air traffic management, payload limitations, regulatory compliance, and public perception, providing a comprehensive understanding of how drones can reshape last-mile logistics. Methodology: The study employs a multi-faceted approach, combining historical analysis, in-depth case studies, and scenario planning to assess the impact of drone technology on last-mile delivery efficiency, cost optimization, and accessibility. Data is gathered from industry reports, interviews with logistics professionals, and regulatory documents. Thematic analysis is conducted to identify critical patterns, while scenario-based modeling offers insight into the potential outcomes of various integration strategies. A comparative evaluation of existing last-mile delivery methods against drone-based delivery models is also provided. Findings: The research reveals that drone technology offers significant potential for enhancing last-mile delivery efficiency, particularly in urban areas and remote locations, aligning with findings from studies like those by Murray & Chu (2015). However, the study identifies considerable obstacles, including regulatory challenges, limited payload capacities, and public acceptance issues. Solutions such as airspace regulation frameworks, collaborative logistics networks, and advanced battery technologies are highlighted as critical enablers for successful drone integration. Contribution to Theory, Policy and Practice: This study contributes to the growing body of knowledge on drone technology's role in logistics by providing a comprehensive framework for businesses and policymakers to navigate the complexities of drone integration. It recommends actionable steps for integrating drones into last-mile delivery, bridging the gap between theoretical innovation and practical application. It provides policy recommendations for regulatory bodies to develop airspace management systems that support drone operations. For practitioners, the research offers a strategic guide to overcoming operational challenges, facilitating the adoption of drones as a sustainable solution for last-mile delivery.", "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Aeronautics", "Computer science", "Engineering", "Geography", "Geodesy", "Biology" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.47941/ijscl.2286" }, { "id": "https://openalex.org/W4319081557", "doi": "10.1142/s2301385024300014", "title": "A Review on the Truck and Drone Cooperative Delivery Problem", "year": 2023, "publication_date": "2023-02-03", "type": "article", "language": "en", "authors": [ "Ruowei Zhang", "Lihua Dou", "Bin Xin", "Chen Chen", "Fang Yi Deng", "Jie Chen" ], "first_author": "Ruowei Zhang", "venue": "Unmanned Systems", "publisher": "World Scientific", "abstract": "As an emerging delivery style in logistics, the cooperation between trucks and drones can significantly improve the efficiency of parcel delivery, especially in some typical scenes, such as mountainous areas, high buildings, or post-disaster material delivery. In recent years, the truck and drone cooperative delivery problem (TDCDP) has attracted more and more attention from logistic research and commercial sectors. This paper proposes a taxonomy for TDCDP and systematically summarizes the related research. First, the impacts of changes in customers and environments on truck and drone delivery modes are analyzed in detail. Second, by using the proposed taxonomy, the delivery modes in TDCDP are classified into four types: parallel delivery, mixed delivery, drone delivery with truck-assisting, and truck delivery with drone-assisting. The roles of trucks and drones are analyzed in different scenes. Then, for different delivery modes, this paper summarizes the TDCDP models and analyzes the common assumptions, constraints, and objective functions. This paper also combs the exact algorithms, heuristic algorithms, and hybrid algorithms used to solve different kinds of TDCDP. Finally, the current research status and future research trends are discussed, and the challenges of TDCDP are highlighted.", "keywords": [ "Drone", "Truck", "Computer science", "Heuristic", "Operations research", "Engineering", "Artificial intelligence", "Aerospace engineering" ], "cited_by_count": 60, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1142/s2301385024300014" }, { "id": "https://openalex.org/W4376271333", "doi": "10.1080/01605682.2023.2210604", "title": "The cost of carrier consistency: Last-mile delivery by vehicle and drone for subscription-based orders", "year": 2023, "publication_date": "2023-05-12", "type": "article", "language": "en", "authors": [ "Amro M. El-Adle", "Ahmed Eisa Ghoniem", "Mohamed Haouari" ], "first_author": "Amro M. El-Adle", "venue": "Journal of the Operational Research Society", "publisher": "Palgrave Macmillan", "abstract": "We investigate a deterministic last-mile delivery problem in which a firm delivering scheduled orders determines a subset of customers to be prioritized for drone delivery, relegating the rest to vehicle delivery. The vehicle and drone deliver in tandem over a planning horizon. The problem is amenable to a multi-day Traveling Salesman Problem with Drone, with consistency in the assignment of customers to each carrier across all days. We develop a mixed-integer program (MIP) that yields provably optimal solutions for instances having up to 40 customers over a 6-day horizon. We also devise a heuristic underpinned by the MIP to effectively and accurately prioritize customers for drone delivery. A computational study involving instances with up to 150 customers ordering over 6 days shows the matheuristic often matching the results of the proposed MIP, and also reveals a logistical burden of less than 0.5% on average over a solution lacking carrier consistency..", "keywords": [ "Drone", "Computer science", "Last mile (transportation)", "Heuristics", "Integer programming", "Travelling salesman problem", "Heuristic", "Operations research", "Time horizon", "Matching (statistics)", "Consistency (knowledge bases)", "Vehicle routing problem" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/01605682.2023.2210604" }, { "id": "https://openalex.org/W2953134621", "doi": "10.1080/01605682.2019.1621671", "title": "Cooperative route planning for the drone and truck in delivery services: A bi-objective optimisation approach", "year": 2019, "publication_date": "2019-06-17", "type": "article", "language": "en", "authors": [ "Kangzhou Wang", "Biao Yuan", "Mengting Zhao", "Yuwei Lu" ], "first_author": "Kangzhou Wang", "venue": "Journal of the Operational Research Society", "publisher": "Palgrave Macmillan", "abstract": "The deployment of drones to support the last-mile delivery has been initially attempted by several companies such as Amazon and Alibaba. The complementary capabilities of the drone and the truck pose an innovative delivery mode. The relevant optimisation problem associated with this new mode, known as the travelling salesman problem with drone (TSP-D), aims to find the coordinated routes of a drone and a truck to serve a list of customers. In practice, managers sometimes intend to attain a compromise between operational cost and completion time. Therefore, this article addresses a bi-objective TSP-D considering both objectives. An improved non-dominated sorting genetic algorithm (INSGA-II) is proposed to solve the problem. Specifically, the label algorithm-based decoding method, the fast non-dominated sorting approach, the crowding-distance computation procedure, and the local search component are devised to accommodate the features of the problem. Furthermore, the first Pareto front obtained by the INSGA-II is improved by a post-optimisation component. Computational results validate the competitive performance of the proposed algorithm. Meanwhile, the trade-off analysis demonstrates the relationship between operational cost and completion time and provides managerial insights for managers designing reasonable compromise routes.", "keywords": [ "Drone", "Computer science", "Compromise", "Operations research", "Genetic algorithm", "Software deployment", "Truck", "Sorting", "Travelling salesman problem", "Component (thermodynamics)", "Last mile (transportation)", "Engineering" ], "cited_by_count": 106, "is_retracted": false, "is_paratext": false, "open_access_url": "http://ir.lzu.edu.cn/handle/262010/295466" }, { "id": "https://openalex.org/W3039927678", "doi": "10.1109/vtc2020-spring48590.2020.9129495", "title": "Unmanned Aerial Vehicles for Package Delivery and Network Coverage", "year": 2020, "publication_date": "2020-05-01", "type": "conference-paper", "language": "en", "authors": [ "Mohammadjavad Khosravi", "Hossein Pishro-Nik" ], "first_author": "Mohammadjavad Khosravi", "venue": null, "publisher": null, "abstract": "Unmanned aerial vehicles(UAVs) have become important in many application fields including last-mile deliveries, surveillance and monitoring, and wireless networks. This paper aims to design UAVs that simultaneously perform multiple tasks. We aim to design UAV trajectories that minimize package delivery time, and at the same time provide uniform coverage over a neighborhood area which is needed for applications such as network coverage or surveillance. First, we study multi task UAVs for a simplified scenario where the neighborhood area is a circular region with the post office located at its center and the houses are assumed to be uniformly distributed on the circle boundary. We propose a trajectory process such that if according to which the drones move, a uniform coverage can be achieved while the delivery efficiency (delivery time with respect to unconstrained case) tends to 1. Second, we consider a more practical scenario in which the delivery destinations are arbitrarily distributed in an arbitrarily-shaped region. We also do not assume any restrictions on the package arrivals. We show that simultaneous uniform coverage and efficient package delivery is possible for such realistic scenarios.", "keywords": [ "Computer science", "Drone", "Trajectory", "Last mile (transportation)", "Process (computing)", "Real-time computing", "Boundary (topology)", "Wireless network", "Wireless", "Computer network", "Simulation", "Mile" ], "cited_by_count": 34, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/vtc2020-spring48590.2020.9129495" }, { "id": "https://openalex.org/W4409710710", "doi": "10.3390/drones9040280", "title": "Integrating Autonomous Vehicles and Drones for Last-Mile Delivery: A Routing Problem with Two Types of Drones and Multiple Visits", "year": 2025, "publication_date": "2025-04-07", "type": "article", "language": "en", "authors": [ "Jili Kong", "Minhui Xie", "Hao Wang" ], "first_author": "Jili Kong", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "With the growing demand for delivery services and the escalating labor costs, much effort has been made to achieve faster and cost-efficient delivery. A promising emerging strategy involves the integration of autonomous delivery vehicles or drones into the last-mile delivery. This study presents a fully automated last-mile delivery system that synergistically integrates autonomous vehicles and drones. We also introduce a novel variant of the vehicle routing problem with drones, referred to as the hybrid autonomous vehicle-drone routing problem (HAVDRP). In HAVDRP, we employ three delivery tools: autonomous vehicles, vehicle-carried drones, and independent drones. The aim is to fully leverage the advantages of autonomous vehicles and drones to provide customers with more efficient last-mile delivery services. An improved adaptive large neighborhood search algorithm is developed to address this problem. The algorithm incorporates a tabu list and an adaptive mechanism specifically designed for the HAVDRP, thereby augmenting the search efficiency. Computational experiments are conducted to evaluate the efficiency of the designed algorithm. Additionally, sensitivity analyses are conducted to explore the influences of some key parameters on the total time, which includes the cumulative working time of autonomous vehicles and drones. Based on the results of sensitivity analyses, we propose some management recommendations for the fully automated last-mile delivery system utilizing autonomous vehicles and drones.", "keywords": [ "Drone", "Mile", "Routing (electronic design automation)", "Last mile (transportation)", "Computer science", "Aeronautics", "Engineering", "Computer network", "Geography", "Biology" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/9/4/280/pdf?version=1744183678" }, { "id": "https://openalex.org/W4285138305", "doi": "10.1007/978-3-030-98872-2_12", "title": "An Application of Interval Valued Pythagorean Fuzzy WASPAS Method for Drone Selection to Last Mile Delivery Operations", "year": 2022, "publication_date": "2022-01-01", "type": "book-chapter", "language": "en", "authors": [ "Ahmet Aktaş", "Mehmet Kabak" ], "first_author": "Ahmet Aktaş", "venue": "Multiple criteria decision making", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Pythagorean theorem", "Selection (genetic algorithm)", "Interval (graph theory)", "Fuzzy logic", "Operations research", "Computer science", "Engineering", "Mathematics", "Artificial intelligence" ], "cited_by_count": 13, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-030-98872-2_12" }, { "id": "https://openalex.org/W4391735860", "doi": "10.1016/j.ejor.2024.02.010", "title": "Hybrid truck-drone delivery system with multi-visits and multi-launch and retrieval locations: Mathematical model and adaptive variable neighborhood search with neighborhood categorization", "year": 2024, "publication_date": "2024-02-11", "type": "article", "language": "en", "authors": [ "Batool Madani", "Malick Ndiaye", "Saı̈d Salhi" ], "first_author": "Batool Madani", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Computer science", "Heuristic", "Operations research", "Variable neighborhood search", "Metaheuristic", "Mathematical optimization", "Artificial intelligence", "Engineering", "Mathematics" ], "cited_by_count": 51, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ejor.2024.02.010" }, { "id": "https://openalex.org/W2910160837", "doi": "10.2514/6.2019-2095", "title": "Design Methodology for Heavy-Lift Unmanned Aerial Vehicles with Coaxial Rotors", "year": 2019, "publication_date": "2019-01-06", "type": "conference-paper", "language": "en", "authors": [ "Wayne Ong", "Spot Srigrarom", "Henrik Hesse" ], "first_author": "Wayne Ong", "venue": "AIAA Scitech 2019 Forum", "publisher": null, "abstract": "This work presents a novel design methodology for multirotor Unmanned Aerial Vehicles (UAVs). To specifically address the design of vehicles with heavy lift capabilities, we have extended existing design methodologies to include coaxial rotor systems which have exhibit the best thrust-to-volume ratio for operation of UAVs in urban environments. Such coaxial systems, however, come with decreased aerodynamic efficiency and the design approach developed in this work can account for this. The proposed design methodology and included market studies have been demonstrated for the development of a multi-parcel delivery drone that can deliver up to four packages using a novel morphing concept. Flight test results in this paper serve to validate the predictions of thrust and battery life of the coaxial propulsion system suggesting errors in predicted flight time of less than 5 percent.", "keywords": [ "Coaxial", "Aerospace engineering", "Lift (data mining)", "Marine engineering", "Aeronautics", "Automotive engineering", "Computer science", "Engineering", "Environmental science", "Electrical engineering" ], "cited_by_count": 42, "is_retracted": false, "is_paratext": false, "open_access_url": "http://eprints.gla.ac.uk/view/author/38965.html>" }, { "id": "https://openalex.org/W3004562173", "doi": null, "title": "Using drones in the last-mile logistics processes of medical product delivery: A feasibility case study in Rotterdam", "year": 2020, "publication_date": "2020-01-12", "type": "conference-paper", "language": "en", "authors": [ "Irene Zubin", "Bart van Arem", "Bart Wiegmans", "Ron van Duin" ], "first_author": "Irene Zubin", "venue": "Research Repository (Delft University of Technology)", "publisher": "Delft University of Technology", "abstract": "The term last-mile delivery refers to the final leg of a business-to-customer service, in which products are shipped from a depot to a destination point bymeans of land transportation, such as vans and small trucks. Although these vehicles provide a common and easy way to consign products, companies are striving for new transport technologies to reduce congestion, infrastructure limitations and air pollution. An alternative to road-bounded vehicles that has recently gained attention is the adoption of drones in parcel delivery. Drone applications range from military training, surveillance, path recognition and shipment of perishable products in emergency situations. Research on drones as delivery vehicles is still in its early stages, with some practical trials carried out by leader companies such as Google and Amazon. However, the application of drones in the pharmaceutical sector for home deliveries of medical products, has not been investigated yet. To gain new insights into the feasibility of introducing drones in the delivery fleet, drone applications were studied for the delivery operations of the pharmacy BENU ’t Slag, in Rotterdam. Two scenario alternatives were tested using the Vehicle Routing Problem formulation. A Large-scale Neighborhood Search algorithm was implemented to solve the problem and derive the performance indicators associated with each scenario. Performances were then analyzed through a comparative analysis. When drones were introduced in the delivery fleet, indicators showed improvements in environmental aspects, service time and delivery costs, with a reduction of 9% in CO2 emissions, 12% in service time and 5.6% in cost per item.", "keywords": [ "Drone", "Service (business)", "Last mile (transportation)", "Truck", "Product (mathematics)", "Transport engineering", "Business", "Computer science", "Operations research", "Marketing", "Mile", "Engineering" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "http://resolver.tudelft.nl/uuid:9ccd09cd-608a-489e-b50d-5dbe3483a80e" }, { "id": "https://openalex.org/W3184244855", "doi": "10.1109/med51440.2021.9480332", "title": "Parcel Delivery with Drones: Multi-criteria Analysis of Trendy System Architectures", "year": 2021, "publication_date": "2021-06-22", "type": "conference-paper", "language": "en", "authors": [ "Graziana Cavone", "Nicola Epicoco", "Raffaele Carli", "Anna Del Zotti", "João Paulo Pereira", "Mariagrazia Dotoli" ], "first_author": "Graziana Cavone", "venue": null, "publisher": null, "abstract": "New technologies, such as Unmanned Aerial Vehicles (UAVs), are transforming facilities and vehicles into intelligent systems that will significantly modify logistic deliveries in any organization. With the appearance of automated vehicles, drones offer multiple new technological solutions that might trigger different delivery networks or boost new delivery services. Differently from the related works, where a single specific delivery system model is typically addressed, this paper deals with the use of UAVs for logistic deliveries focusing on a multi-criteria analysis of trendy drone-based system architectures. In particular, using the cross-efficiency Data Envelopment Analysis approach, a comparative analysis among three different delivery systems is performed: the classic system based on trucks only, the drone-only system using a fleet of drones, and the hybrid truck and drone system combining trucks and drones. The proposed technique constitutes an effective decision-making tool aimed at helping delivery companies in selecting the optimal delivery system architecture according to their specific needs. The effectiveness of the proposed methodology is shown by a simulation analysis based on a realistic data case study that pertains to the main logistic service providers.", "keywords": [ "Drone", "Truck", "Computer science", "Architecture", "Service (business)", "Operations research", "Systems engineering", "Engineering", "Business", "Automotive engineering" ], "cited_by_count": 19, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/10198/23883" }, { "id": "https://openalex.org/W4392719414", "doi": "10.1109/tits.2024.3371189", "title": "Communication-Aware Drone Delivery Problem", "year": 2024, "publication_date": "2024-03-12", "type": "article", "language": "en", "authors": [ "Cihan Tugrul Cicek", "Çağrı Koç", "Hakan Gültekin", "Güneş Erdoğan" ], "first_author": "Cihan Tugrul Cicek", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The drone delivery problem (DDP) has been introduced to include aerial vehicles in last-mile delivery operations to increase efficiency. However, the existing studies have not incorporated the communication quality requirements of such a delivery operation. This study introduces the communication-aware DDP (C-DDP), which incorporates handover and outage constraints into the conventional multi-depot multi-trip green vehicle routing problem with time windows. In particular, any trip of a drone to deliver a customer package must require less than a certain number of handover operations and cannot exceed a predefined outage duration threshold. A mixed integer programming (MIP) model is developed to minimize the total flight distance while satisfying communication constraints. We present a genetic algorithm (GA) that can solve large instances and compare its performance with an off-the-shelf MIP solver. Computational study shows that the GA and MIP solver performances are equivalent to solving smaller instances. We also compare the GA performance against another evolutionary algorithm, particle swarm optimization (PSO), for larger instances and find that the GA outperforms the PSO with slightly longer CPU times. The results indicate that ignoring the communication constraints would cause significant operational disruption risk and this risk can be easily mitigated with a slight sacrifice from flight distances by incorporating the proposed communication constraints. In particular, the communication performance can be improved by up to 28.9% when the flight distance is increased by 19.1% at most on average.", "keywords": [ "Drone", "Computer science", "Engineering", "Aeronautics" ], "cited_by_count": 14, "is_retracted": false, "is_paratext": false, "open_access_url": "https://researchportal.bath.ac.uk/en/publications/6d231b3b-bf92-4c68-b2d2-3d10eeb2528e" }, { "id": "https://openalex.org/W7138846745", "doi": "10.1287/msom.2025.0055", "title": "Frontiers in Operations: Last-Mile Delivery in Healthcare: Drone Delivery for Blood Products in Rwanda", "year": 2026, "publication_date": "2026-03-19", "type": "article", "language": "en", "authors": [ "H. Harriet Jeon", "Claudio Lucarelli", "Jean Baptiste Mazarati", "Donatien Ngabo", "Hummy Song" ], "first_author": "H. Harriet Jeon", "venue": "Manufacturing & Service Operations Management", "publisher": "Institute for Operations Research and the Management Sciences", "abstract": "Problem definition: Last-mile delivery is one of the most challenging and costly facets of the supply chain. Using data from Rwandan public hospitals that transfuse blood, we examine whether and the extent to which the adoption of a technological innovation—delivery drones—for the last-mile delivery of blood products impacts the way hospitals manage the inventory of these products and the downstream health outcomes for patients. Methodology/results: To estimate causal effects, we exploit the staggered rollout of the drone delivery system and use a generalized difference-in-differences approach. We find that all hospitals, regardless of their distance to the drone port, substantially decrease their on-hand inventory of red blood cells, most notably for the most flexible product (i.e., type O blood). Hospitals also meaningfully reduce their wastage of red blood cells, especially for “in-between” products that are neither the most flexible nor the least flexible (i.e., type B blood). With respect to patient health outcomes, we document large reductions in in-hospital mortality for two health conditions where timely access to blood is a critical input for treatment: postpartum hemorrhage and trauma. Interestingly, this change is concentrated among hospitals closer to the drone port, and these are the same set of hospitals that increase the transfusion of blood products. This increase is especially pronounced among blood products that cannot be held in stock at the hospital, including platelets and fresh frozen plasma. Managerial implications: Our results highlight key considerations for decision makers allocating scarce resources to improve hospital operations and health outcomes. Given that health improvements are not realized by all hospitals, operational decisions—such as the number and location of drone ports—should ensure clinically meaningful delivery windows for time-sensitive medical care. History: This paper has been accepted in the Manufacturing & Service Operations Management Frontiers in Operations Initiative. Funding: This work was supported by the Wharton Dean’s Research Fund, Wharton Global Initiatives Research Program, Claude Marion Endowed Faculty Scholar Award, Mack Institute Research Fellowship, and Fishman-Davidson Center for Service and Operations Management. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2025.0055 .", "keywords": [ "Drone", "Supply chain", "Health care", "Product (mathematics)", "Exploit", "Public health", "Blood product", "Stock (firearms)" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1287/msom.2025.0055" }, { "id": "https://openalex.org/W4395003697", "doi": "10.3390/math12081250", "title": "Risk Analysis of the Use of Drones in City Logistics", "year": 2024, "publication_date": "2024-04-20", "type": "article", "language": "en", "authors": [ "Snežana Radoman Tadić", "Mladen Dragan Krstić", "Miloš Veljović", "Olja Čokorilo", "Milica Milovanović" ], "first_author": "Snežana Radoman Tadić", "venue": "Mathematics", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Drone delivery in city logistics is gaining attention due to road congestion, environmental threats, etc. However, there are risks associated with using drones which can result in hazardous events, such as conflicts in the air, loss of control, and system failures. It is crucial to assess the risks involved in using different types of drones and choose the option with the lowest risk. The existence of different criteria important for this decision imposes the need to apply the multi-criteria decision-making (MCDM) method(s). This paper proposes a new hybrid model that combines the fuzzy Factor Relationship (FARE) method for obtaining the criteria weights and the Axial Distance-based Aggregated Measurement (ADAM) method for obtaining the final ranking of the alternatives. A single-rotor microdrone weighing up to 4.4 lb was chosen as the optimal solution, and after that, the most favorable are also the drones of this size (multi-rotor and fixed-wing microdrones). The establishment of a novel hybrid MCDM model, the identified risks, the set of criteria for evaluating the least risky drones, and the framework for prioritizing the drones are the main novelties and contributions of the paper.", "keywords": [ "Drone", "Business", "Biology", "Genetics" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2227-7390/12/8/1250/pdf?version=1713602675" }, { "id": "https://openalex.org/W4403398619", "doi": "10.56578/judm030304", "title": "Optimising Drone-Assisted Logistics for Urban Last-Mile Delivery: An Overview of Applications, Methodologies, and Emerging Trends", "year": 2024, "publication_date": "2024-09-10", "type": "article", "language": "en", "authors": [ "Antonio Pratelli", "Lorenzo Brocchini", "Massimiliano Petri" ], "first_author": "Antonio Pratelli", "venue": "Journal of Urban Development and Management", "publisher": null, "abstract": "The rapid evolution of drone-assisted logistics for urban last-mile (ULM) delivery has garnered significant interest from both academia and industry. This article presents a comprehensive review of the state-of-the-art research and practical implementations of ULM systems, focusing on the use of unmanned aerial vehicles (UAVs) for the final stage of goods and parcel delivery in urban environments. The applicability of UAV-based logistics across various contexts, including urban and rural areas, is examined, with real-world case studies highlighted to demonstrate practical uses. Key methodologies and models employed in optimising UAV routing and operations are discussed, particularly those that enhance the efficiency and reliability of ULM. The critical advantages and limitations of drone-assisted last-mile logistics are analysed, providing insights into the operational, regulatory, and technological challenges. The discussion is further expanded by addressing emerging trends in UAV technology, as well as innovations in drone deployment strategies and the evolving regulatory landscape. In conclusion, potential theoretical advancements and future applications of ULM systems are outlined, with an emphasis on integrating drones into broader logistics networks and smart city frameworks. The insights offered aim to guide future research and practical developments in this rapidly advancing field.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "City logistics", "Aeronautics", "Engineering", "Computer science", "Transport engineering", "Geography" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://library.acadlore.com/JUDM/2024/3/3/JUDM_03.03_04.pdf" }, { "id": "https://openalex.org/W4200506244", "doi": "10.1016/j.trc.2021.103506", "title": "Point-to-point drone-based delivery network design with intermediate charging stations", "year": 2021, "publication_date": "2021-12-20", "type": "article", "language": "en", "authors": [ "Roberto Pinto", "Alexandra Lagorio" ], "first_author": "Roberto Pinto", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Last mile (transportation)", "Computer science", "Heuristic", "Process (computing)", "Operations research", "Network planning and design", "Point (geometry)", "Perspective (graphical)", "Transport engineering", "Mile", "Engineering" ], "cited_by_count": 86, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2021.103506" }, { "id": "https://openalex.org/W4406764075", "doi": "10.1007/s10732-024-09543-0", "title": "Transforming last mile delivery with heterogeneous assistants: drones and delivery robots", "year": 2025, "publication_date": "2025-01-23", "type": "article", "language": "en", "authors": [ "Cheng Chen", "Emrah Demir", "Xi Hu", "Hainan Huang" ], "first_author": "Cheng Chen", "venue": "Journal of Heuristics", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Computer science", "Robot", "Aeronautics", "Engineering", "Geography", "Artificial intelligence", "Biology" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10732-024-09543-0" }, { "id": "https://openalex.org/W3177299951", "doi": null, "title": "Potential Benefits of Drones for Vaccine Last-Mile Delivery in Nepal", "year": 2021, "publication_date": "2021-06-09", "type": "dissertation", "language": "en", "authors": [ "Adriana Lembcke Berninzon", "Ornipha Vongasemjit" ], "first_author": "Adriana Lembcke Berninzon", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Geography", "Aeronautics", "Engineering", "Computer security", "Computer science", "Biology", "Genetics" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://dspace.mit.edu/handle/1721.1/130957" }, { "id": "https://openalex.org/W4386820358", "doi": "10.1016/j.trc.2023.104333", "title": "When drone delivery meets human courier: A co-sourcing perspective", "year": 2023, "publication_date": "2023-09-18", "type": "article", "language": "en", "authors": [ "Zhi Pei", "Yunduo Liu", "Xu Dai", "Yilun Yuan", "Changchun Liu" ], "first_author": "Zhi Pei", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Profitability index", "Queue", "Operations research", "Profit (economics)", "Queueing theory", "Mathematical optimization", "Revenue", "Business", "Economics", "Microeconomics" ], "cited_by_count": 20, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2023.104333" }, { "id": "https://openalex.org/W4386839006", "doi": "10.1016/j.trc.2023.104322", "title": "The drone latency location routing problem under uncertainty", "year": 2023, "publication_date": "2023-09-15", "type": "article", "language": "en", "authors": [ "Maria Elena Bruni", "Sara Khodaparasti", "Guido Perboli" ], "first_author": "Maria Elena Bruni", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": "This paper addresses a location routing problem arising in the last-mile drone delivery context, where drones are used to deliver small packages to a set of customers. Each drone is launched from a fulfillment center to serve multiple customers on a single trip. The goal is to find the optimal subset of fulfillment centers to use as drone launching and landing platforms and the optimal drone routes with the aim of minimizing the sum of customers’ waiting times. We study the problem under two realistic assumptions. First, the drone energy consumption is a nonlinear function of the drone load that varies along the route, as parcels are delivered. Second, the drone flight time is not deterministically known. To hedge against drone flight time uncertainty, we adopt a robust optimization approach. Due to the complex nature of the problem, which turns out to be a nonlinear mixed-integer problem, we design an exact method based on a tailored efficient Branch & Check algorithm that uses customized no-good cuts. The computational experiments show the validity of the proposed model and the promising performance of the exact method. Moreover, we present a case study on last-mile parcel delivery in Turin, Italy, providing insights into the advantages of a drone-based delivery system.", "keywords": [ "Drone", "Computer science", "Context (archaeology)", "Mathematical optimization", "Routing (electronic design automation)", "Operations research", "Real-time computing", "Engineering", "Computer network", "Mathematics", "Geography" ], "cited_by_count": 48, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2023.104322" }, { "id": "https://openalex.org/W4408300770", "doi": "10.1016/j.sftr.2025.100536", "title": "Prioritizing sustainable solutions to mitigate risks in drone-based last-mile delivery", "year": 2025, "publication_date": "2025-03-10", "type": "article", "language": "en", "authors": [ "Chandresh B. Kumbhani", "Ravi Kant", "Ravi Shankar" ], "first_author": "Chandresh B. Kumbhani", "venue": "Sustainable Futures", "publisher": "Elsevier BV", "abstract": "• We propose sustainable solutions to mitigate drone delivery risks. • Spherical fuzzy sets are used to handle uncertainty and hesitation. • Fuzzy C-means clustering is used for clustering drone delivery risks and solutions. • This framework is most suitable for drone practitioners and government authorities. The drone integration into last-mile delivery networks presents substantial opportunities for enhancing sustainability and efficiency. However, drone integration into the existing logistics framework presents numerous risks, particularly operational safety and reliability. This study addresses these gaps by proposing a novel hybrid framework for systematically evaluating and mitigating risks in drone-based sustainable last-mile delivery. This framework incorporates spherical fuzzy decision-making trial and evaluation laboratory (SF-DEMATEL), spherical fuzzy C-means clustering (SFCMC), and spherical fuzzy evaluation based on distance from average solution (SF-EDAS) using the Indian logistics sector as a case study. The results reveal that technical-related risks, customer adoption risks, and government rules and regulatory risks are critical risk clusters for drones in the last-mile delivery applications. Significant DDSs are strict regulations from the government being the most crucial, followed by provide public education and awareness and workforce retraining. Sensitivity and comparative analysis are conducted to validate the robustness of the framework. This approach holds promise for decision-makers, researchers, practitioners, and stakeholders in the drone industry seeking to make informed choices about risk mitigation strategies.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Business", "Aeronautics", "Engineering", "Geography", "Biology" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.sftr.2025.100536" }, { "id": "https://openalex.org/W3128023699", "doi": "10.1109/twc.2021.3054748", "title": "Multi-Purpose Drones for Coverage and Transport Applications", "year": 2021, "publication_date": "2021-02-03", "type": "article", "language": "en", "authors": [ "Mohammadjavad Khosravi", "Saeede Enayati", "Hamid Saeedi", "Hossein Pishro-Nik" ], "first_author": "Mohammadjavad Khosravi", "venue": "IEEE Transactions on Wireless Communications", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Unmanned aerial vehicles (UAVs) have become important in many applications including last-mile deliveries, surveillance and monitoring, and wireless networks. This paper aims to design UAV trajectories that simultaneously perform multiple tasks. We aim to design UAV trajectories that efficiently perform some transportation operation (e.g., package delivery), and at the same time provide uniform coverage over a neighborhood area which is needed for applications such as network coverage, Internet of Things (IoT) devices data collection, wireless power transfer, and surveillance. We first consider multi-task UAVs for a simplified scenario where the neighborhood area is a circular region where UAV missions start from the center and the destinations are assumed to be uniformly distributed on the circle boundary. We propose a trajectory process such that if according to which the UAV's move, a uniform coverage can be achieved while the transport (delivery) efficiency is still preserved. We then consider a more practical scenario in which the transport destinations are arbitrarily distributed in an arbitrarily-shaped region. We show that simultaneous uniform coverage and efficient transport trajectory (e.g. package delivery) is possible for such realistic scenarios. This is shown using both rigorous analysis as well as simulations.", "keywords": [ "Computer science", "Drone", "Trajectory", "Last mile (transportation)", "Wireless", "Process (computing)", "Wireless network", "Real-time computing", "Computer network", "Distributed computing", "Mile", "Telecommunications" ], "cited_by_count": 44, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/twc.2021.3054748" }, { "id": "https://openalex.org/W3030830012", "doi": "10.1016/j.micpro.2020.103142", "title": "Towards a framework of key technologies for drones", "year": 2020, "publication_date": "2020-05-25", "type": "article", "language": "en", "authors": [ "Réda Nouacer", "Mahmoud M. Hussein", "Huáscar Espinoza", "Yassine Ouhammou", "Matheus Ladeira", "Rodrigo Castiñeira" ], "first_author": "Réda Nouacer", "venue": "Microprocessors and Microsystems", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Computer science", "Key (lock)", "Drone", "Computer security" ], "cited_by_count": 56, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/am/pii/S0141933120303094" }, { "id": "https://openalex.org/W4319046426", "doi": "10.1016/j.techsoc.2023.102203", "title": "Urban drone adoption: Addressing technological, privacy and task–technology fit concerns", "year": 2023, "publication_date": "2023-01-25", "type": "article", "language": "en", "authors": [ "Le Yi Koh", "Jia Yi Lee", "Xueqin Wang", "Kum Fai Yuen" ], "first_author": "Le Yi Koh", "venue": "Technology in Society", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Structural equation modeling", "Task (project management)", "Technology acceptance model", "Last mile (transportation)", "Perception", "Pandemic", "Theory of planned behavior", "Business", "Perspective (graphical)", "Marketing", "Internet privacy" ], "cited_by_count": 65, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.techsoc.2023.102203" }, { "id": "https://openalex.org/W4293765590", "doi": "10.1109/tits.2021.3119080", "title": "Hybrid Multi-Objective Optimization Approach With Pareto Local Search for Collaborative Truck-Drone Routing Problems Considering Flexible Time Windows", "year": 2021, "publication_date": "2021-10-20", "type": "article", "language": "en", "authors": [ "Qizhang Luo", "Guohua Wu", "Bin Ji", "Ling Wang", "Ponnuthurai Nagaratnam Suganthan" ], "first_author": "Qizhang Luo", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The collaboration of drones and trucks for last-mile delivery has attracted much attention. In this paper, we address a collaborative routing problem of the truck-drone system, in which a truck collaborates with multiple drones to perform parcel deliveries and each customer can be served earlier and later than the required time with a given tolerance. To meet the practical demands of logistics companies, we build a multi-objective optimization model that minimizes total distribution cost and maximizes overall customer satisfaction simultaneously. We propose a hybrid multi-objective genetic optimization approach incorporated with a Pareto local search algorithm to solve the problem. Particularly, we develop a greedy-based heuristic method to create initial solutions and introduce a problem-specific solution representation, genetic operations, as well as six heuristic neighborhood strategies for the hybrid algorithm. Besides, an adaptive strategy is adopted to further balance the convergence and the diversity of the hybrid algorithm. The performance of the proposed algorithm is evaluated by using a set of benchmark instances. The experimental results show that the proposed algorithm outperforms three competitors. Furthermore, we investigate the sensitivity of the proposed model and hybrid algorithm based on a real-world case in Changsha city, China.", "keywords": [ "Vehicle routing problem", "Pareto principle", "Truck", "Computer science", "Mathematical optimization", "Hybrid algorithm (constraint satisfaction)", "Genetic algorithm", "Drone", "Local search (optimization)", "Heuristic", "Greedy algorithm", "Multi-objective optimization" ], "cited_by_count": 122, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2021.3119080" }, { "id": "https://openalex.org/W4387747530", "doi": "10.1016/j.ejor.2023.10.021", "title": "The multi-visit drone-assisted pickup and delivery problem with time windows", "year": 2023, "publication_date": "2023-10-18", "type": "article", "language": "en", "authors": [ "Shanshan Meng", "Yanru Chen", "Dong Li" ], "first_author": "Shanshan Meng", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Truck", "Vehicle routing problem", "Context (archaeology)", "Operations research", "Pickup", "Mathematical optimization", "Routing (electronic design automation)", "Engineering", "Mathematics", "Automotive engineering" ], "cited_by_count": 79, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ejor.2023.10.021" }, { "id": "https://openalex.org/W4288047872", "doi": "10.1109/icuas54217.2022.9836198", "title": "Building Trust with a Mobile Application for Last-Mile Commercial Drone Delivery", "year": 2022, "publication_date": "2022-06-21", "type": "conference-paper", "language": "en", "authors": [ "Jurgen Famula", "Daniel E. Pittman", "Kerstin S. Haring" ], "first_author": "Jurgen Famula", "venue": "2022 International Conference on Unmanned Aircraft Systems (ICUAS)", "publisher": null, "abstract": "A common set of problems faced by commercial delivery companies are to find ways to increase the efficiency and reliability of the \"last mile\" of a package’s journey, all while reducing operating costs. This has driven many companies to start exploring using Unmanned Aerial Vehicles (UAVs), or drones, as a means to get packages to their final destination. While UAVs have a great potential to help increase efficiency in commercial package delivery, this comes at a potential cost of the privacy of people intersecting the flight paths of these unmanned vehicles. This paper explores public user perception of the expected privacy that a mobile phone application for commercial delivery drones could offer, in order to determine what privacy measures should be implemented to engender trust in unmanned delivery platforms. We found that for a commercial drone delivery system to be adopted by the general public, safety and privacy risks remain one of the biggest hurdles for trust and acceptance, and we found evidence that a user-centered mobile application could increase trust in commercial drone flights.", "keywords": [ "Drone", "Mobile phone", "Mile", "Phone", "Reliability (semiconductor)", "Last mile (transportation)", "Computer science", "Delivery Performance", "Computer security", "Order (exchange)", "Internet privacy", "Business" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/icuas54217.2022.9836198" }, { "id": "https://openalex.org/W4402454303", "doi": "10.1108/k-04-2024-1098", "title": "Flying to your home yard: the mediation and moderation model of the intention to employ drones for last-mile delivery", "year": 2024, "publication_date": "2024-09-11", "type": "article", "language": "en", "authors": [ "Abdul Hafaz Ngah", "Thurasamy Ramayah", "Samar Rahi", "Nurul Izni Kamalrulzaman", "Aamir Rashid", "Fei Long" ], "first_author": "Abdul Hafaz Ngah", "venue": "Kybernetes", "publisher": "Emerald Publishing Limited", "abstract": "Purpose Drones will become part of daily lives similar to smartphones becoming a staple of modern living. Nonetheless, only several past studies investigated the intention to utilise drones for parcel delivery however, the intention to use drones among online shoppers was not fully explored. The study attempts to investigate the factors influencing the intention to use drones for last-mile delivery. Design/methodology/approach A total of 292 data were gathered via an online survey among online shoppers applying a snowball sampling method. Since the study operationalised the measures as composites, a combination of reflective and formative measurement, and the study focusses on predictive purposes, partial least squares structural equation modelling with SmartPLS 4 was applied to test the model developed based on the stimulus-organism-response model. Findings The analysis found that all the direct hypotheses were found supported. Moreover, Green support, green desire and pro-environmental behaviour positively and sequentially mediated future orientation and intention, whereas technology anxiety and perceived safety moderated the relationship between pro-environmental behaviour and intention. Research limitations/implications The respondents only limit to the online shoppers in Malaysia which based on purposive sampling method, thus the findings cannot be generalized to another countries. Practical implications Besides enriching the literature on drone studies, the findings provided practical insights to online platforms and drone operators to develop an effective strategy to encourage online shoppers to shift from conventional delivery to drone delivery. Originality/value The study developed a new model for drone delivery studies using the S-O-R model in introducing orientation towards the future and green support as the stimulus, green desire as an organism and pro-environmental behaviour and usage intention as a response. The study introduced multiple sequential mediators, also contributing to the S-O-R model to predict online shoppers' behaviour towards drones as a tool for last-mile delivery. Another important contribution, technology anxiety and perceived safety were confirmed to have a moderation effect for the relationship between pro-environmental behaviour and intention to use drones for last-mile delivery.", "keywords": [ "Drone", "Last mile (transportation)", "Yard", "Mile", "Moderation", "Mediation", "Computer science", "Dredging", "Food delivery", "Moderated mediation", "Simulation", "Advertising" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1108/k-04-2024-1098" }, { "id": "https://openalex.org/W2200876215", "doi": "10.6084/m9.figshare.1300003.v1", "title": "Unmanned Aerial Vehicle and Geospatial Technology Pushing the Limits of Development", "year": 2015, "publication_date": "2015-02-03", "type": "article", "language": "en", "authors": [ "Journal Ajer", "Tiwari Abhilasha Dixit Anuj" ], "first_author": "Journal Ajer", "venue": null, "publisher": null, "abstract": "Often referred to as unmanned aerial vehicles, or UAVs, drones were most commonly associated with military or police operations but with advancement in information technology in last two decades, cheaper and smaller sensors, better integration and ease-of-use options this tool is start revolutionizing the way geospatial data is collected in many countries, monitoring large, rugged areas, tracking down criminals, observing forest fires and disaster areas. Beyond just viewing the result, with the use of photogrammetry, image processing and ground control points, the captured imagery could provide a base for collecting all the 2D and 3D features that are the last-mile problem in modeling and visualizing the whole world. The research aims to understand various characteristics of this emerging technology that makes it the most promising geospatial and attribute data collection tool in GIS community. Second aim of this paper is to explore the possible applications of UAV in the developing country like India.", "keywords": [ "Geospatial analysis", "Drone", "Photogrammetry", "Aerial survey", "Geomatics", "Computer science", "Geographic information system", "Remote sensing", "Geography", "Data science" ], "cited_by_count": 32, "is_retracted": false, "is_paratext": false, "open_access_url": "https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/1878820/C0401016021.pdf" }, { "id": "https://openalex.org/W3157568166", "doi": "10.1371/journal.pone.0250737", "title": "A decentralized hybrid computing consumer authentication framework for a reliable drone delivery as a service", "year": 2021, "publication_date": "2021-04-30", "type": "article", "language": "en", "authors": [ "Abdul Hannan", "Faisal Bashir Hussain", "Noman Ali", "Muhammad Ehatisham-ul-Haq", "Muhammad Usman Ashraf", "Ahmed Mohammed Alghamdi", "Ahmed Saeed Alfakeeh" ], "first_author": "Abdul Hannan", "venue": "PLoS ONE", "publisher": "Public Library of Science", "abstract": "The thriving adoption of drones for delivering parcels, packages, medicines, etc., is surging with time. The application of drones for delivery services results in faster delivery, fuel-saving, and less energy consumption. Giant companies like Google, Amazon, Facebook, etc., are actively working on developing, testing, and improving drone-based delivery systems. So far, a lot of work has been done for improving the design, speed, operating range, security of the delivery drones, etc. However, very limited work has been done to ensure a complete and reliable last-mile delivery from the merchant's store to the hands of the actual customer. To ensure a complete and reliable last-mile delivery, a drone must authenticate the consumer before dropping the package. Therefore, in this work, we propose a consumer authentication (Consumer-Auth) hybrid computing framework for drone delivery as a service to make sure that the parcel is perfectly delivered to the intended customer. The proposed Consumer-Auth framework enables a drone to reach the exact destination by using the GPS coordinates of the customer autonomously. After reaching the exact location, the drone waits for the customer to come to the specific pinned location then it starts a two-factor consumer authentication process, i.e., one-time password (OTP) verification and face Recognition. The experimental results manifest the effectiveness of the proposed Consumer-Auth framework to ensure a complete and reliable drone-based last-mile delivery.", "keywords": [ "Drone", "Computer science", "Last mile (transportation)", "Authentication (law)", "Password", "Computer security", "Service (business)", "Process (computing)", "Mile", "Business", "Marketing", "Operating system" ], "cited_by_count": 20, "is_retracted": false, "is_paratext": false, "open_access_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0250737&type=printable" }, { "id": "https://openalex.org/W4280559245", "doi": "10.1007/s00291-022-00680-1", "title": "The traveling salesman problem with drone resupply", "year": 2022, "publication_date": "2022-05-11", "type": "article", "language": "en", "authors": [ "Michael Dienstknecht", "Nils Boysen", "Dirk Briskorn" ], "first_author": "Michael Dienstknecht", "venue": "OR Spectrum", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Travelling salesman problem", "Drone", "Truck", "Context (archaeology)", "Computer science", "Operations research", "Schedule", "Traveling purchaser problem", "Aeronautics", "2-opt", "Engineering", "Automotive engineering" ], "cited_by_count": 42, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s00291-022-00680-1" }, { "id": "https://openalex.org/W4392623442", "doi": "10.1002/ett.4958", "title": "DAC‐MD : A privacy preserving drone‐access control scheme for last mile delivery", "year": 2024, "publication_date": "2024-03-01", "type": "article", "language": "en", "authors": [ "Azeem Irshad", "Muhammad Farooq", "Khalid Mahmood", "Ghulam Ali Mallah", "Shehzad Ashraf Chaudhry" ], "first_author": "Azeem Irshad", "venue": "Transactions on Emerging Telecommunications Technologies", "publisher": null, "abstract": "Abstract The service delivery has lately witnessed strides in the form of paradigm shifts from conventional logistics to drone‐oriented supply chain to conserve ecosystem. The use of drones or unmanned aerial vehicles (UAVs) for package deliveries offer enhanced accessibility, flexibility, efficiency, speed, safety, and even few environmental gains. However, the drones can come across various security hazards while communicating with ground installations on open channels including physical capture attack, privacy infringement, and so on. Thus, earnest endeavors are needed to fix those security challenges in applications related to drone communications. To address these problems, an efficient authenticated key agreement technique, drone access control scheme for last mile delivery (DAC‐MD) is suggested for user‐drone interactions in IoD environment that help the participating entities in developing a mutually agreed session key for securing subsequent communication interactions. The proposed scheme is proved using automated ProVerif tool as well as analyzed by using formal analysis based on RoR random oracle model. The comparative analysis against recently presented known studies reveals that our scheme not only carries comparable properties in terms of security and privacy, but also low computational and communication costs.", "keywords": [ "Drone", "Mile", "Scheme (mathematics)", "Computer science", "Last mile (transportation)", "Control (management)", "Computer security", "Internet privacy", "Geography", "Biology", "Mathematics", "Artificial intelligence" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/ett.4958" }, { "id": "https://openalex.org/W4206099505", "doi": "10.1109/ieem50564.2021.9672856", "title": "Extending the Last Mile Delivery Routing Problem for Enhancing Sustainability by Drones Using a Sentiment Analysis Approach", "year": 2021, "publication_date": "2021-12-13", "type": "conference-paper", "language": "en", "authors": [ "Edy Anas Ahmadi", "Hendro Wicaksono", "Omid Fatahi Valilai" ], "first_author": "Edy Anas Ahmadi", "venue": "2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)", "publisher": null, "abstract": "Last mile delivery is of important stages through supply chains and logistics, which covers the final stage of delivering products to the end customers. With the growth of e-commerce and the increasing desire of people to shopping online, logistics and consequently last mile delivery became very important. One of the biggest challenges is the issue of sustainability and reducing pollution when delivering products to customers, especially in urban surroundings. For this reason, this study presents a new model that considers the issue of sustainability in optimising the problem of vehicle routing problem with drones. For this purpose, a sentiment analysis is used considering Twitter to determine the alignment of customer sentiments on environmental protection and to calculate the net promoter score index. This index is considered as a coefficient in the penalty function added to the base model. According to the results of this study, this new model will be applied to logistics companies that are responsible for the issue of sustainability and can help customers who are willing to participate for improving the sustainability of the supply chain.", "keywords": [ "Sustainability", "Last mile (transportation)", "Drone", "Reverse logistics", "Supply chain", "Index (typography)", "Business", "Computer science", "Environmental economics", "Mile", "Marketing", "Economics" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/ieem50564.2021.9672856" }, { "id": "https://openalex.org/W4389166357", "doi": "10.1155/2023/7399080", "title": "Factors Influencing Technology Acceptance of Drones for Last-Mile Food Deliveries: An Adaptation of the UTAUT2 Model", "year": 2023, "publication_date": "2023-11-30", "type": "article", "language": "en", "authors": [ "Asish Oommen Mathew", "Srijit Chowdhury", "Sanjivani Devpura", "Anasuya Kulshekar Lingappa" ], "first_author": "Asish Oommen Mathew", "venue": "Human Behavior and Emerging Technologies", "publisher": "Wiley", "abstract": "As the food delivery sector grows in importance, new delivery modes to address service issues, such as costs, swift delivery, and environmental concerns, are being researched. However, research on drone-based food delivery services is still lacking, especially in the Indian context, which the current study aims to address. The study furthered the UTAUT2 model with additional perceived risk and price sensitivity constructs. Quantitative, cross-sectional data was collected nationwide using convenience sampling through online survey questionnaires. The 323 responses were analyzed using the partial least square-structural equation modeling method. The results identified effort expectancy, social influence, and hedonic motivation as significant predictors of attitude and behavioral intention. In an emerging economy with a vast consumer base, this study may offer a preliminary standpoint for understanding the consumer perspective on drone food deliveries. The findings of this study might be necessary for businesses that deal with food delivery logistics as a point of view to formulate successful strategies.", "keywords": [ "Unified theory of acceptance and use of technology", "Expectancy theory", "Structural equation modeling", "Context (archaeology)", "Marketing", "Business", "Drone", "Psychology", "Computer science", "Geography", "Social psychology" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://downloads.hindawi.com/journals/hbet/2023/7399080.pdf" }, { "id": "https://openalex.org/W4410445584", "doi": "10.3390/electronics14102026", "title": "Machine Learning-Driven Truck–Drone Collaborative Delivery for Time- and Energy-Efficient Last-Mile Deliveries", "year": 2025, "publication_date": "2025-05-16", "type": "article", "language": "en", "authors": [ "Didem Cicek", "Murat Şimşek", "Burak Kantarcı" ], "first_author": "Didem Cicek", "venue": "Electronics", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Truck–drone collaboration in urban last-mile deliveries offers an innovative solution to address inefficiencies in modern supply chain networks. This work leverages real drone flight data to train a machine learning-based drone energy model that accurately estimates the time and energy consumption of drones to support resource-related decisions. An AI engine is proposed that integrates the drone energy model with a self-organizing feature map algorithm, ensuring continuous drone operation without reliance on charging infrastructure. A total of 93 comprehensive scenario-based simulations over 1 week of delivery data in MATLAB offers actionable insights into resource allocation, demonstrating that deploying three drones at five truck stops results in the most energy-efficient delivery scenario, reducing energy consumption by 36% compared to the least efficient outcome, in which a single drone is deployed at four stops. The holistic and data-driven approach to truck-drone collaboration presented in this work has the potential to bridge the gap between theoretical models and real-world applications.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Truck", "Aeronautics", "Engineering", "Computer science", "Transport engineering", "Automotive engineering", "Simulation", "Geography" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2079-9292/14/10/2026/pdf?version=1747384676" }, { "id": "https://openalex.org/W4241930935", "doi": "10.37624/ijert/13.10.2020.2824-2830", "title": "Unmanned Aerial Vehicle (UAV) for Parcel Delivery", "year": 2020, "publication_date": "2020-10-31", "type": "article", "language": "en", "authors": [ "Neha Gupta", "Rosey Chauhan", "Shikha Chadha" ], "first_author": "Neha Gupta", "venue": "International Journal of Engineering Research and Technology", "publisher": "International Research Publication House", "abstract": "Air Drones, Unmanned Aerial Vehicles (UAV), autonomous or tele-operated flying machines are the aircrafts that doesn't require a human onboard for controlling it.They can be managed manually by a remote wireless operator or automatically using the software.Our purpose in this paper is to present the use of drones for parcels and small packages delivery that can be used commercially or in emergency situations.A drone that is capable of lifting weights up to 1 -1.5 kg, an autonomous system that would control the drone completely using the Raspberry Pi a microprocessor that will connect the drone to the control system and will control the drone throughout the process.A Global Positioning System (GPS) that helps the drone to reach its destination and return to the base station.This paper presents how drones would be helpful in delivering small packages helping ecommerce expand their business, and also can used to deliver in emergency situations like deliveries of blood, medicinal goods and many other items that a person or professional can use in emergency, which takes lot of time currently for a person to deliver by hand.", "keywords": [ "Computer science", "Aeronautics", "Marine engineering", "Aerospace engineering", "Environmental science", "Engineering" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.37624/ijert/13.10.2020.2824-2830" }, { "id": "https://openalex.org/W4212847014", "doi": "10.1016/j.apm.2022.02.024", "title": "Simultaneous cooperation of Refrigerated Ground Vehicle (RGV) and Unmanned Aerial Vehicle (UAV) for rapid delivery with perishable food", "year": 2022, "publication_date": "2022-02-19", "type": "article", "language": "en", "authors": [ "Seung Yeob Lee", "So Rim Han", "Byung Duk Song" ], "first_author": "Seung Yeob Lee", "venue": "Applied Mathematical Modelling", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Integer programming", "Food delivery", "Computer science", "Linear programming", "Transport engineering", "Operations research", "Engineering", "Algorithm", "Business" ], "cited_by_count": 36, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.apm.2022.02.024" }, { "id": "https://openalex.org/W4409075262", "doi": "10.1016/j.tre.2025.104095", "title": "Data-driven optimization for drone delivery service planning with online demand", "year": 2025, "publication_date": "2025-04-02", "type": "article", "language": "en", "authors": [ "Aditya Paul", "Michael W. Levin", "Steven Travis Waller", "David Rey" ], "first_author": "Aditya Paul", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": "In this study, we develop an innovative data-driven optimization approach to solve the drone delivery service planning problem with online demand. Drone-based logistics are expected to improve operations by enhancing flexibility and reducing congestion effects induced by last-mile deliveries. With rising digitalization and urbanization, however, logistics service providers are constantly grappling with the challenge of uncertain real-time demand. This study investigates the problem of planning drone delivery service through an urban air traffic network to fulfill dynamic and stochastic demand. Customer requests – if accepted – generate profit and are serviced by individual drone flights as per request origins, destinations and time windows. We cast this stochastic optimization problem as a Markov decision process . We present a novel data-driven optimization approach which generates predictive prescriptions of parameters of a surrogate optimization formulation. Our solution method consists of synthesizing training data via lookahead simulations to train a supervised machine learning model for predicting relative link priority based on the state of the network. This knowledge is then leveraged to selectively create weighted reserve capacity in the network and via a surrogate objective function that controls the trade-off between reserve capacity and profit maximization to maximize the cumulative profit earned. Using numerical experiments based on benchmarking transportation networks, the resulting data-driven optimization policy is shown to outperform a myopic policy. Sensitivity analyses on learning parameters reveal insights into the design of efficient policies for drone delivery service planning with online demand.", "keywords": [ "Drone", "Service (business)", "Computer science", "Business", "On demand", "Operations research", "Engineering", "Marketing", "Multimedia" ], "cited_by_count": 19, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2025.104095" }, { "id": "https://openalex.org/W4392945845", "doi": "10.1109/icst59744.2023.10460847", "title": "Aerodynamics and Sensing Analysis for Efficient Drone-Based Parcel Delivery", "year": 2023, "publication_date": "2023-12-17", "type": "conference-paper", "language": "en", "authors": [ "Avishkar Seth", "Alice James", "Endrowednes Kuantama", "Subhas Chandra Mukhopadhyay", "Richard Y. Han" ], "first_author": "Avishkar Seth", "venue": null, "publisher": null, "abstract": "In an era of rapid urbanization and e-commerce growth, efficient parcel delivery methods are crucial. This paper presents a detailed study of the aerodynamics and sensing analysis of drones for parcel delivery. Utilizing Computational Fluid Dynamics (CFD), the study offers a comprehensive airflow analysis, revealing the aerodynamic forces affecting drone stability due to payload capacity. A multidisciplinary approach is employed, integrating mechanical design, control theory, and sensing systems to address the complex issue of parcel positioning. The experimental validation section rigorously tests different size payloads and their positions and impact on drones with maximum thrusts of 2000 gf. The findings prove the drone’s capacity to lift a large payload that covers up to 50 percent of the propeller, thereby contributing to optimizing drone designs and sustainable parcel delivery systems. It has been observed that the drone can lift a large payload smoothly when placed above the drone, with an error rate as low as 0.1 percent for roll, pitch, and yaw. This work paved the way for more versatile, real-world applications of drone technology, setting a new standard in the field.", "keywords": [ "Drone", "Payload (computing)", "Aerodynamics", "Computer science", "Aerospace engineering", "Lift (data mining)", "Computational fluid dynamics", "Simulation", "Marine engineering", "Engineering", "Computer security" ], "cited_by_count": 17, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2410.20584" }, { "id": "https://openalex.org/W2771137816", "doi": null, "title": "Drones for Commercial Last-Mile Deliveries: A Discussion of Logistical, Environmental, and Economic Trade-Offs", "year": 2017, "publication_date": "2017-01-01", "type": "article", "language": "en", "authors": [ "Miguel Figliozzi" ], "first_author": "Miguel Figliozzi", "venue": "PDXScholar (Portland State University)", "publisher": "Portland State University", "abstract": "There are no studies that model the potential effectiveness of Unmanned Aerial Vehicles (UAVs) or drones to reduce CO2e lifecycle (including both utilization and vehicle phase) emissions when compared to conventional diesel vans, electric trucks, electric vans, and tricycles. This study presents a novel analysis of lifecycle UAV and ground commercial vehicles CO2e emissions.", "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Business", "Geography" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=1430&context=cengin_fac" }, { "id": "https://openalex.org/W4406972807", "doi": "10.1007/978-3-031-78238-1_36", "title": "Last Mile Drone Delivery: Complexity and Research Challenges", "year": 2025, "publication_date": "2025-01-01", "type": "conference-paper", "language": "en", "authors": [ "Fatos Xhafa", "Cristian Domínguez", "Angel Alejandro Juan" ], "first_author": "Fatos Xhafa", "venue": "Lecture notes in computer science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Computer science", "Mile", "Last mile (transportation)", "Geography" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-78238-1_36" }, { "id": "https://openalex.org/W3091900884", "doi": "10.3390/su12208318", "title": "Model of Third-Party Risk Index for Unmanned Aerial Vehicle Delivery in Urban Environment", "year": 2020, "publication_date": "2020-10-09", "type": "article", "language": "en", "authors": [ "Xinhui Ren", "Caixia Cheng" ], "first_author": "Xinhui Ren", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "In order to assess the airspace risk of unmanned aerial vehicles (UAVs) operating at low altitudes, the third-party risks of UAV urban operations were defined: the risks caused by drones to people on the ground who are not involved in operations and do not profit from operations, and the sources and objects of the risk were clarified. Taking into account the drone crash, noise, on-board camera, and ground environment factors, a UAV urban logistics risk index evaluation model was constructed. First, the UAV image regression model was used to construct a three-dimensional grid, and then a comprehensive third-party risk index model of UAV urban logistics was built based on the casualty and noise risks. Finally, the Southern District of Civil Aviation University of China was selected as an example scene, and surface data were obtained through a field investigation and instrument measurements. Then, the risk of drone operations in the airspace 30–60 m above this area was evaluated. The results showed that the third-party risk was lower when the UAV flying altitude above a building was greater. However, in other areas such as lakes, woods, roads, open spaces, a lower flight altitude had a lower risk. A comparison of the whole airspace showed that the third-party risk was the lowest when the drone operated at an altitude of 30 m. The results also showed that the third-party risk above the lake and greenery was the lowest when on the same plane, followed by the lower risk above the buildings and open squares, with the highest third-party risk above the canteen passage.", "keywords": [ "Drone", "Civil aviation", "Index (typography)", "Transport engineering", "Computer science", "Aeronautics", "Aviation", "Engineering", "Aerospace engineering" ], "cited_by_count": 37, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/12/20/8318/pdf?version=1602495593" }, { "id": "https://openalex.org/W4307552321", "doi": "10.3390/drones6110321", "title": "Unmanned Aerial Vehicle Adaptation to Facilitate Healthcare Supply Chains in Low-Income Countries", "year": 2022, "publication_date": "2022-10-26", "type": "article", "language": "en", "authors": [ "Kalani Gunaratne", "Amila Thibbotuwawa", "Alex Elkjær Vasegaard", "Peter Nielsen", "H. Niles Perera" ], "first_author": "Kalani Gunaratne", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Low-income countries are persistently suffering from last-mile logistics issues in healthcare supply chains. Therefore, it is high time to explore technological applications to overcome such inadequacies. The faster speed, low maintenance cost, and absence of road dependency in unmanned aerial vehicles (UAV) have popularized them as an alternative to road delivery. Hence, it is suggested as a solution to overcome the persisting distribution inefficiencies in healthcare logistics of low-income countries. According to the case study analysis conducted on the Sri Lankan vaccine cold chain, incorporating UAVs increases truck-space utilization and reduces the time consumed, cost incurred, and carbon dioxide emission in a delivery round. Moreover, the most suitable way to cover the initial setup cost of an unmanned aerial system (UAS) is by receiving aid from international donors. The capital cost also can be covered by government investments or via service outsourcing only if the number of flights per year is increased. Moreover, a homogenous (i.e., only UAV) solution was revealed to be more beneficial than a heterogeneous (i.e., truck and UAV) solution. However, due to the lack of technology literacy and willingness to change in low-income countries, it is recommended to initially execute a heterogeneous solution and expand to a homogeneous plan in the future years. However, it was evident that for a mixed-fleet solution to be advantageous, drone characteristics play a vital role. Hence, a UAV with specifications ideal for the use case must be utilized to garner the maximum benefits. Nevertheless, it was apparent that with the right implementation plan, UAVs possess the potential to overcome the shortcomings in the healthcare logistics of low-income countries.", "keywords": [ "Business", "Truck", "Supply chain", "Drone", "Environmental economics", "Operations management", "Economics", "Engineering", "Marketing" ], "cited_by_count": 39, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/6/11/321/pdf?version=1667817450" }, { "id": "https://openalex.org/W4392858165", "doi": "10.1016/j.vehcom.2024.100761", "title": "Crowdsourced vehicles and UAVs for last-mile delivery application using blockchain-hosted matching mechanism", "year": 2024, "publication_date": "2024-03-15", "type": "article", "language": "en", "authors": [ "Maha Kadadha", "Rabeb Mizouni", "Shakti Singh", "Hadi Otrok", "Azzam Mourad" ], "first_author": "Maha Kadadha", "venue": "Vehicular Communications", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Crowdsourcing", "Computer science", "Blockchain", "Last mile (transportation)", "Matching (statistics)", "Supply chain", "Mile", "Computer security", "Business", "World Wide Web" ], "cited_by_count": 14, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.vehcom.2024.100761" }, { "id": "https://openalex.org/W2915502992", "doi": "10.20944/preprints201902.0183.v1", "title": "Two-Echelon Routing Problem for Parcel Delivery by Cooperated Truck and Drone", "year": 2019, "publication_date": "2019-02-19", "type": "preprint", "language": "en", "authors": [ "Yao Liu", "Jianmai Shi", "Guohua Wu", "Zhong Liu", "Witold Pedrycz" ], "first_author": "Yao Liu", "venue": "Preprints.org", "publisher": null, "abstract": "A new variant of two-echelon routing problem is investigated, where the truck and the drone are used to cooperatively complete the deliveries of all parcels. The truck not only acts as a tool for parcel delivery, but also serves as a moving depot for the drone. The drone can carry several parcels and take off from the truck, while returning to the truck after completing the delivery. The energy consumption model for the routing process of the drone is analyzed, when it is utilized to deliver multiple parcels. A two-stage route-based modelling approach is proposed to optimize both the truck’s main route and the drone’s adjoint flying routes. A hybrid heuristic integrating nearest neighbor and cost saving strategies is developed to quickly construct a feasible solution. The simulated annealing algorithm is applied to improve the quality of the solution, where a Tabu list is employed to improve the search efficiency. Random instances at different scales are used to test the performance of the proposed algorithm. A case study based on the practical road network in Changsha, China, is presented, through which the sensitivity analysis is conducted with respect to some critical factors.", "keywords": [ "Drone", "Truck", "Simulated annealing", "Routing (electronic design automation)", "Tabu search", "Computer science", "Vehicle routing problem", "Heuristic", "Process (computing)", "Operations research", "Transport engineering", "Engineering" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.preprints.org/manuscript/201902.0183/v1/download" }, { "id": "https://openalex.org/W4285090396", "doi": "10.3390/en15145074", "title": "The Impact of Airspace Discretization on the Energy Consumption of Autonomous Unmanned Aerial Vehicles (Drones)", "year": 2022, "publication_date": "2022-07-12", "type": "article", "language": "en", "authors": [ "Mo ElSayed", "Moataz Mohamed" ], "first_author": "Mo ElSayed", "venue": "Energies", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Promising massive emissions reduction and energy savings, the utilization of autonomous unmanned aerial vehicles (UAVs) in last-mile parcel delivery is continuously expanding. However, the limited UAV range deters their widescale adoption to replace ground modes of transportation. Moreover, real-world data on the impact of different parameters on the operation, emissions, and energy consumption is scarce. This study aims to assess the impact of airspace planning and discretization on the energy consumption of autonomous UAVs. We utilize a novel open-source comprehensive UAV autonomous programming framework and a digital-twin model to simulate real-world three-dimensional operation. The framework integrates airspace policies, UAV kinematics, and autonomy to accurately estimate the operational energy consumption via an experimentally verified energy model. In the simulated case study, airspace is discretized by both a traditional Cartesian method and a novel dynamic 4D discretization (Skyroutes) method. This allows for the comparison of different routing and trajectory planning algorithms for ten missions. The results show a variation in the energy consumption by up to 50%, which demonstrates the criticality of airspace discretization and planning on UAV charging infrastructure design, greenhouse gas emissions reduction, and airspace management.", "keywords": [ "Energy consumption", "Discretization", "Drone", "Computer science", "Automotive engineering", "Engineering" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1996-1073/15/14/5074/pdf?version=1657616573" }, { "id": "https://openalex.org/W4383901091", "doi": "10.1016/j.retrec.2023.101325", "title": "The sustainable hybrid truck-drone delivery model with stochastic customer existence", "year": 2023, "publication_date": "2023-07-11", "type": "article", "language": "en", "authors": [ "Ebrahim Teimoury", "Reza Rashid" ], "first_author": "Ebrahim Teimoury", "venue": "Research in Transportation Economics", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Payload (computing)", "Computer science", "Heuristic", "Operations research", "Markov chain", "Order (exchange)", "Operational efficiency", "Mathematical optimization", "Automotive engineering", "Engineering" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.retrec.2023.101325" }, { "id": "https://openalex.org/W4362635965", "doi": "10.1016/j.swevo.2023.101295", "title": "Solving electric vehicle–drone routing problem using memetic algorithm", "year": 2023, "publication_date": "2023-04-05", "type": "article", "language": "en", "authors": [ "Setyo Tri Windras Mara", "Ruhul Amin Sarker", "Daryl Essam", "Saber Mohammed Elsayed" ], "first_author": "Setyo Tri Windras Mara", "venue": "Swarm and Evolutionary Computation", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Memetic algorithm", "Computer science", "Routing (electronic design automation)", "Set (abstract data type)", "Electric vehicle", "Vehicle routing problem", "Integer programming", "Mathematical optimization", "Battery (electricity)", "Algorithm", "Local search (optimization)" ], "cited_by_count": 64, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.swevo.2023.101295" }, { "id": "https://openalex.org/W4400651090", "doi": "10.1108/jamr-03-2024-0103", "title": "Ranking the benefits of drone-based last-mile delivery due to adoption of its enablers", "year": 2024, "publication_date": "2024-07-15", "type": "article", "language": "en", "authors": [ "Chandresh B. Kumbhani", "Ravi Kant" ], "first_author": "Chandresh B. Kumbhani", "venue": "Journal of Advances in Management Research", "publisher": "Emerald Publishing Limited", "abstract": "Purpose Strategic integration of enablers and the realization of drone delivery benefits emerge as essential strategies for business organizations to enhance operational efficiency and stay competitive in last-mile logistics. This paper aims to explore the benefits of drone-based last-mile delivery in the Indian logistic sector by providing a framework for ranking drone delivery benefits (DDBs) due to the adoption of its enablers. Design/methodology/approach This study proposes a novel hybrid framework applied in the Indian logistic sector by integrating a sentence boundary extraction algorithm for extracting benefits from literature, a spherical fuzzy analytical hierarchy process (SF-AHP) for evaluating primary enablers, unsupervised fuzzy C-means clustering (FCM) for clustering benefits and a spherical combined compromised solution (SF-CoCoSo) for ranking benefits with respect to primary enablers. Findings The results reveal that technological and infrastructure enablers (TIE), government and legislation enablers (GLE) and operational and service quality enablers (OSE) are the most significant enablers for drone implementation in logistics. Top-ranked benefits increase the efficiency of last-mile delivery (DDB10), foster supply chain management and logistic sustainability (DDB16) and increase delivery access to rural area and vulnerable people (DDB17). Practical implications This research assists scholars, entrepreneurs and policymakers in the sustainable deployment of drone delivery in the logistics sector. This study facilitates the use of drones in delivery services and provides a foundation for all stakeholders in logistics. Originality/value The assessments involve considering judgment from a highly knowledgeable and experienced group in India, characterized by a large volume of inputs and a high level of expertise.", "keywords": [ "Drone", "Last mile (transportation)", "Ranking (information retrieval)", "Business", "Process management", "Sustainability", "Stakeholder", "Service delivery framework", "Service (business)", "Marketing", "Computer science", "Economics" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1108/jamr-03-2024-0103" }, { "id": "https://openalex.org/W4311272603", "doi": "10.1016/j.trip.2022.100708", "title": "A drone hop from the local shop? Where could drone delivery as a service happen in Europe and the USA, and how many people could benefit from it?", "year": 2022, "publication_date": "2022-12-01", "type": "article", "language": "en", "authors": [ "Jean-Philippe Aurambout", "Konstantinos Gkoumas", "Biagio Ciuffo" ], "first_author": "Jean-Philippe Aurambout", "venue": "Transportation Research Interdisciplinary Perspectives", "publisher": "Elsevier BV", "abstract": "The rapid technological and regulatory evolution in the field of autonomous unmanned aerial vehicles (UAV or drones) may soon open the way for their deployment in the last mile delivery of products. This has the potential to decrease delivery costs, reduce transport externalities caused by road traffic and reduce missed-deliveries. It could thus become a disruptor to the parcel delivery industry and for this reason several transport and delivery companies are piloting experiments involving drones. Yet a detailed analysis of the market potential of this system is still only partly available in the literature. To bridge this gap, this paper tries to quantify the proportion of the population, both in Europe and the USA that could benefit from drone-delivery services. Results indicate that under the conditions considered drone delivery services could be financially viable in the Europe and in the USA, where they could serve between 16 and 43% and between 32 and 60% of the population respectively. These results indicate the viability of this industry in the near future, highlighting that the existing geographical distribution of populations has a significant influence and will likely drive the choice of the first deployments.", "keywords": [ "Drone", "Software deployment", "Population", "Business", "Last mile (transportation)", "Transport engineering", "Engineering", "Mile", "Geography" ], "cited_by_count": 17, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2590198222001683/pdf" }, { "id": "https://openalex.org/W4386955371", "doi": "10.1016/j.cor.2023.106435", "title": "The drone-assisted pickup and delivery problem: An adaptive large neighborhood search metaheuristic", "year": 2023, "publication_date": "2023-09-22", "type": "article", "language": "en", "authors": [ "Timothy Mulumba", "Waleed Najy", "Ali H. Diabat" ], "first_author": "Timothy Mulumba", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Metaheuristic", "Computer science", "Pickup", "Benchmarking", "Operations research", "Integer programming", "Last mile (transportation)", "Vehicle routing problem", "Routing (electronic design automation)", "Artificial intelligence" ], "cited_by_count": 49, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cor.2023.106435" }, { "id": "https://openalex.org/W4411996646", "doi": "10.1109/tem.2025.3584730", "title": "A Bane or Boon of Technologies: Risks and Benefits of Drone Delivery on Last-Mile Operations", "year": 2025, "publication_date": "2025-01-01", "type": "article", "language": "en", "authors": [ "Eric Ka Ho Leung", "Xin Wen" ], "first_author": "Eric Ka Ho Leung", "venue": "IEEE Transactions on Engineering Management", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Drones for logistics operations have emerged as a popular topic in logistics, offering numerous benefits and risks to the society and environment. While drones can have a significant impact on the surroundings, the environment and external factors can also influence drone delivery operations, resulting in a complex interplay. This paper combines a comprehensive literature review and co-citation analysis, supplemented by practices, to explore the two-way interaction between drones and the environment. The benefits and risks of this interaction are also examined. A trend analysis is further conducted to generate insights regarding the stages of development in the literature. Combining findings from the reviewed literature and practices, we propose the novel 3R framework to guide future drone delivery adoption in practical operations. This framework highlights the importance of investigating drone delivery models and their respective risks that should be mitigated. Finally, a future research agenda is proposed to inspire further explorations in this rapidly evolving field of last-mile operations.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "Aeronautics", "Engineering", "Computer science", "Business", "Geography" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tem.2025.3584730" }, { "id": "https://openalex.org/W4401384371", "doi": "10.1177/03063070241269379", "title": "Drone delivery and consumer behavior in last mile logistics: an empirical study in South Korea", "year": 2024, "publication_date": "2024-08-07", "type": "article", "language": "en", "authors": [ "Woohyoung Kim", "Yu Liu", "Miao Su", "Feng Liu", "Mingjie Fang" ], "first_author": "Woohyoung Kim", "venue": "Journal of General Management", "publisher": "SAGE Publishing", "abstract": "Despite the great potential that drone technology can bring to last-mile logistics, consumers’ intent to use it appears to be lower than expected. Therefore, this study investigated the factors influencing consumers’ intentions to use drone delivery. A theoretical model based on value–belief–norm theory was developed and tested with structural equation modeling based on data collected from 458 Korean consumers. The results suggest that the environmental protection, economic, and altruistic values of drone delivery positively impact consumers’ perceptions of responsibility. In addition, the ascription of responsibility positively influences consumers’ personal norms. Finally, personal norms are found to increase consumers’ intentions to use drone delivery, and the impact is positively moderated by moral obligation. This study employs the extended value–belief–norm (VBN) framework and makes a valuable contribution to the existing body of literature. Furthermore, this study employs the VBN model to ascertain the ecological advantages associated with environmentally sustainable unmanned aerial vehicles (UAVs). Additionally, it provides valuable practical implications for professionals and policymakers in the field.", "keywords": [ "Drone", "Ascription", "Structural equation modeling", "Moral obligation", "Theory of planned behavior", "Marketing", "Last mile (transportation)", "Business", "Perception", "Value (mathematics)", "Advertising", "Mile" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1177/03063070241269379" }, { "id": "https://openalex.org/W7127588952", "doi": "10.3390/logistics10020038", "title": "Sustainable and Safe Last-Mile Delivery: A Multi-Objective Truck–Drone Matheuristic", "year": 2026, "publication_date": "2026-02-04", "type": "article", "language": "en", "authors": [ "Armin Mahmoodi", "Mehdi Davoodi", "Said M. Easa", "Seyed Mojtaba Sajadi" ], "first_author": "Armin Mahmoodi", "venue": "Logistics", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Background: The rapid growth of e-commerce has intensified the need for last-mile delivery systems that can navigate urban congestion while minimizing environmental impact. Hybrid truck–drone networks offer a promising solution by combining heavy-duty ground transport with aerial flexibility; however, their deployment faces significant challenges in jointly managing operational risks, energy limits, and regulatory compliance. Methods: This study proposes a hybrid matheuristic framework to solve this multi-objective problem, simultaneously minimizing transportation cost, service time, energy consumption, and operational risk. A two-phase approach combines a metaheuristic for initial truck routing with a Mixed-Integer Linear Programming (MILP) formulation for optimal drone assignment and scheduling. This decomposition strikes a balance between exact optimization and computational scalability. Results: Experiments across various instance sizes (up to 100 customers) and fleet configurations demonstrate that integrating MILP enhances solution diversity and convergence compared to standalone strategies. Sensitivity analyses reveal significant impacts of drone speed and endurance on system efficiency. Conclusions: The proposed framework provides a practical decision-support tool for balancing complex trade-offs in time-sensitive, risk-constrained delivery environments, thereby contributing to more informed urban logistics planning.", "keywords": [ "Software deployment", "Truck", "Drone", "Convergence (economics)", "Linear programming", "Traffic congestion", "Routing (electronic design automation)", "Service (business)", "Vehicle routing problem" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2305-6290/10/2/38/pdf?version=1770201784" }, { "id": "https://openalex.org/W4383894985", "doi": "10.59973/emjsr.11", "title": "Last mile delivery Optimisation model for drone-enabled Vehicle Routing Problem", "year": 2023, "publication_date": "2023-07-11", "type": "article", "language": "en", "authors": [ "Ismail Tausif" ], "first_author": "Ismail Tausif", "venue": "Emerging Minds Journal for Student Research", "publisher": null, "abstract": "In light of e-commerce's exponential growth trajectory over recent years, it has never been more critical to evaluate the last-mile delivery segment for its efficiency and cost-effectiveness. Autonomous vehicles (drones) offer considerable promise as potential solutions with ongoing investigations into emerging technologies in this context. To address problems related to last mile-delivery in logistics operations, the practicality of adopting a hybrid truck-drone delivery system is examined through this study. The researchers utilized Mixed-integer linear programming (MILP)and Gurobi optimization solvers both for optimizing performance as well as facilitating execution. While testing a drone dataset of a well-known logistics company as part of their research using an optimization model, the findings suggested that were remarkable competitive advantages including significant gains in reduction of timing. Nevertheless, there are several constraints like maintenance, recharging, difficult weather conditions & traffic congestion-necessitating focused innovative AI-based approaches. In spite of these impediments, a hybrid truck-drone’s potential applicability can remarkably boost the efficiency of last-mile delivery operations.", "keywords": [ "Drone", "Truck", "Last mile (transportation)", "Computer science", "Context (archaeology)", "Integer programming", "Mile", "Vehicle routing problem", "Operations research", "Transport engineering", "Routing (electronic design automation)", "Linear programming" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ipipublishing.org/index.php/emjsr/article/download/11/14" }, { "id": "https://openalex.org/W3106663860", "doi": "10.2139/ssrn.3564671", "title": "How Drones Can Help Fight the Coronavirus", "year": 2020, "publication_date": "2020-01-01", "type": "preprint", "language": "en", "authors": [ "Brent Skorup", "Connor Haaland" ], "first_author": "Brent Skorup", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Pandemic", "Social distance", "Coronavirus disease 2019 (COVID-19)", "Lexicon", "Dozen", "Business", "2019-20 coronavirus outbreak", "Set (abstract data type)", "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)", "Key (lock)", "Computer security" ], "cited_by_count": 49, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.3564671" }, { "id": "https://openalex.org/W4408050344", "doi": "10.1016/j.cie.2025.111001", "title": "Combining autonomous delivery robots and traditional vehicles with public transportation infrastructure in last-mile distribution", "year": 2025, "publication_date": "2025-02-28", "type": "article", "language": "en", "authors": [ "Gianpaolo Ghiani", "Emanuela Guerriero", "Emanuele Manni", "Deborah Pareo" ], "first_author": "Gianpaolo Ghiani", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": "The recent boom of e-commerce and the resulting concern about emissions increase are promoting the development of alternative paradigms for last-mile delivery, involving greener vehicles, such as air drones and autonomous delivery robots, which are also less sensitive to traffic congestion. In this paper, we study a last-mile distribution problem in which a heterogeneous fleet composed of both traditional vehicles and autonomous delivery robots is used to service a large number of customer requests in an urban area. The delivery robots use stations of the public transportation network as their depots. The problem amounts to building both van and delivery-robot routes in such a way as to minimize the distribution cost, meeting the constraints imposed by the different ranges and capacities of both vehicles. At the same time, another decision involves choosing at which stations of the public transportation network the delivery robots are based. For this purpose, we develop two variants of a matheuristic scheme based on the solution of a hybrid set-partitioning and location-based model. We perform thorough computational experiments on instances inspired by the problem of distributing drugs to pharmacies in the urban area of Rome (Italy) and show that, when the instance size grows, the proposed solution approach allows us to obtain significant cost reductions compared to both a straightforward solution of a mathematical model and a classical metaheuristic scheme. In addition, we show that combining autonomous delivery robots with traditional vehicles allows us to achieve important cost and emission reductions with respect to a traditional delivery scheme.", "keywords": [ "Last mile (transportation)", "Mile", "Transport engineering", "Robot", "Public transport", "Distribution (mathematics)", "Transportation infrastructure", "Engineering", "Business", "Computer science", "Geography", "Artificial intelligence" ], "cited_by_count": 21, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2025.111001" }, { "id": "https://openalex.org/W4387618706", "doi": "10.34293/sijash.v11i2.6650", "title": "Ubiquitous Unmanned Aerial Vehicles (UAVs): A Comprehensive Review", "year": 2023, "publication_date": "2023-10-01", "type": "article", "language": "en", "authors": [ "Ahad Shabib Alotaibi", "Chris R. Chatwin", "Philip M. Birch" ], "first_author": "Ahad Shabib Alotaibi", "venue": "Shanlax International Journal of Arts Science and Humanities", "publisher": null, "abstract": "Unmanned aerial vehicles (UAVs) or drones have found applications in various fields including military operations, construction, parcel delivery, mapping, medical, search and rescue missions, exploration of hidden areas, monitoring power lines and oil rigs, precision farming, aerial surveillance, and wireless communication. Due to their modular flexibility and programmability, drone technologies have become a strategic industrial/commercial sector that has gained significant attention as it redefines and combines different emerging domains, such as: service and delivery convergence, lean manufacturing, environmental monitoring and security. The use of swarms of interconnected UAV systems has gained popularity in providing innovative approaches to tasks requiring wide-area multiple collaborative sensors. However, despite advances in maneuverability, user interface, and cost-effectiveness, drones still face limitations in flight autonomy due to restricted flight time for continuous missions. Battery endurance, drone weight, and payload are critical development vectors. This review highlights the importance of drones, their future development priorities and functionality. Specifically, it focuses on UAV classification, swarms, and charging. Moreover, it explores UAV applications, challenges, and security issues based on recent research and development. Additionally, the study delves into anti-drone technology that can assist countries in controlling and ensuring the safe utilization of drones.", "keywords": [ "Drone", "Payload (computing)", "Flexibility (engineering)", "Modular design", "Computer science", "Systems engineering", "Engineering", "Computer security" ], "cited_by_count": 13, "is_retracted": false, "is_paratext": false, "open_access_url": "https://shanlaxjournals.in/journals/index.php/sijash/article/download/6650/6271" }, { "id": "https://openalex.org/W4404756526", "doi": "10.1016/j.tre.2024.103859", "title": "Air Corridor Planning for Urban Drone Delivery: Complexity Analysis and Comparison via Multi-Commodity Network Flow and Graph Search", "year": 2024, "publication_date": "2024-11-27", "type": "article", "language": "en", "authors": [ "Xinyu He", "Lishuai Li", "Yanfang Mo", "Zhankun Sun", "Shiliang Qin" ], "first_author": "Xinyu He", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Flow network", "Computer science", "Graph", "Transport engineering", "Flow (mathematics)", "Commodity", "Operations research", "Mathematical optimization", "Engineering", "Business", "Theoretical computer science" ], "cited_by_count": 31, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2024.103859" }, { "id": "https://openalex.org/W3155393628", "doi": "10.1016/j.ejor.2021.03.064", "title": "The Piggyback Transportation Problem: Transporting drones launched from a flying warehouse", "year": 2021, "publication_date": "2021-04-13", "type": "article", "language": "en", "authors": [ "Kai Wang", "Erwin Pesch", "Dominik Kreß", "Ilia Fridman", "Nils Boysen" ], "first_author": "Kai Wang", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Launched", "Drone", "Warehouse", "Transport engineering", "Operations research", "Business", "Computer science", "Aeronautics", "Operations management", "Engineering", "Marketing" ], "cited_by_count": 50, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ejor.2021.03.064" }, { "id": "https://openalex.org/W4295858029", "doi": "10.2139/ssrn.4211353", "title": "Parcel Consolidation Approach and Routing Algorithm for Last-Mile Delivery by Unmanned Aerial Vehicles", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Xiaohui Li", "Pengyu Yan", "Kaize Yu", "Peifan Li" ], "first_author": "Xiaohui Li", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Mile", "Consolidation (business)", "Last mile (transportation)", "Computer science", "Routing algorithm", "Vehicle routing problem", "Aeronautics", "Real-time computing", "Routing (electronic design automation)", "Engineering", "Transport engineering", "Computer network" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4211353" }, { "id": "https://openalex.org/W2773333411", "doi": "10.1007/978-3-319-65283-2_24", "title": "Task Allocation of Multiple UAVs for Cooperative Parcel Delivery", "year": 2017, "publication_date": "2017-12-14", "type": "book-chapter", "language": "en", "authors": [ "Gyeongtaek Oh", "Youdan Kim", "Jaemyung Ahn", "Han‐Lim Choi" ], "first_author": "Gyeongtaek Oh", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Payload (computing)", "Task (project management)", "Computer science", "Mathematical optimization", "Limit (mathematics)", "Greedy algorithm", "Integer programming", "Time limit", "Integer (computer science)", "Operations research", "Distributed computing", "Algorithm" ], "cited_by_count": 23, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-319-65283-2_24" }, { "id": "https://openalex.org/W3025493413", "doi": "10.1109/lra.2020.2993757", "title": "A Morphing Cargo Drone for Safe Flight in Proximity of Humans", "year": 2020, "publication_date": "2020-05-12", "type": "article", "language": "en", "authors": [ "Przemyslaw Kornatowski", "Mir Feroskhan", "William J. Stewart", "Dario Floreano" ], "first_author": "Przemyslaw Kornatowski", "venue": "IEEE Robotics and Automation Letters", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Delivery drones used by logistics companies today are equipped with unshielded propellers, which represent a major hurdle for in-hand parcel delivery. The exposed propeller blades are hazardous to unsuspecting bystanders, pets, and untrained users. One solution to provide safety is to enclose a drone with an all-encompassing protective cage. However, the structures of existing cage designs have low density in order to minimize obstruction of propeller airflow, so as to not decrease efficiency. The relatively large openings in the cage do not protect hands and fingers from fast rotating propellers. Here we describe a novel approach to safety and aerodynamic efficiency by means of a high-density cage and morphing arms loosely inspired by the box turtle. The drone cage is made of a dense and lightweight grid. When flying in proximity of humans, the arms and propellers are retracted and fully sealed within the cage, thus making the drone safe and also reducing the total footprint. When flying at cruising altitude far from people and objects, the arms and propellers extend out of the protective grid, thus increasing aerodynamic efficiency by more than 20%.", "keywords": [ "Drone", "Propeller", "Morphing", "Aeronautics", "Marine engineering", "Cage", "Automotive engineering", "Crew", "Grid", "Computer science", "Engineering", "Aerospace engineering" ], "cited_by_count": 53, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/7083369/9059055/09091043.pdf" }, { "id": "https://openalex.org/W4401943231", "doi": "10.1109/tsc.2024.3451243", "title": "A Holistic and Hybrid Service Selection Strategy for MEC-Based UAV Last-Mile Delivery Systems", "year": 2024, "publication_date": "2024-08-28", "type": "article", "language": "en", "authors": [ "Xu Jia", "Xiao Liu", "Azadeh Ghari Neiat", "Liju Chu", "Xuejun Li", "Yun Jin Yang" ], "first_author": "Xu Jia", "venue": "IEEE Transactions on Services Computing", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "With the widespread use of Internet of Things (IoT) technology, an enormous number of end devices that request various kinds of cloud services have been connected to the Internet. Multi-access edge computing (MEC) can reduce the service response time by selecting the required edge computing resources closer to the end device. However, MEC-based smart systems require heterogeneous and diverse services support. Taking unmanned aerial vehicle (UAV) last-mile delivery system as an example, there are two types of services required: delivery and computational services. The edge services in MEC environments are distributed and limited. Inefficient service selection plans will affect the quality of services of such smart systems. Therefore, how to design a suitable service selection strategy is a crucial issue for MEC-based smart systems. To address this issue, we propose a service selection framework and a holistic and hybrid service selection ($H^{2}S^{2}$) strategy for MEC-based UAV last-mile delivery systems in real-world UAV last-mile delivery scenarios. This framework considers three important characteristics of UAV delivery systems: diverse service requirements, service availability, and service mobility. The$H^{2}S^{2}$strategy focuses on selecting the optimal delivery and computational services and provides an integrated approach with a static service selection algorithm and a dynamic service re-selection algorithm. The$H^{2}S^{2}$strategy determines the optimal delivery and computational service selection plans with the lowest UAV energy consumption and shortest service response time. We assess the effectiveness and efficiency of the$H^{2}S^{2}$strategy through ablation studies and comparative analyses with diverse representative strategies. The experimental results show that the$H^{2}S^{2}$strategy improves the effectiveness and efficiency of the UAV delivery system by significantly reducing UAV's energy consumption and service response time.", "keywords": [ "Computer science", "Mile", "Last mile (transportation)", "Selection (genetic algorithm)", "Service (business)", "Computer network", "Artificial intelligence" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://figshare.com/articles/journal_contribution/A_Holistic_and_Hybrid_Service_Selection_Strategy_for_MEC-based_UAV_Last-mile_Delivery_Systems/27100153" }, { "id": "https://openalex.org/W4414179284", "doi": "10.1080/13675567.2025.2549129", "title": "Modeling drone-enabled last-mile blood delivery systems for emergency healthcare", "year": 2025, "publication_date": "2025-09-15", "type": "article", "language": "en", "authors": [ "Yash Daultani", "Felix T.S. Chan", "Saurabh Pratap", "Mohit Goswami" ], "first_author": "Yash Daultani", "venue": "International Journal of Logistics Research and Applications", "publisher": "Taylor & Francis", "abstract": "The management of the blood supply chain is of vital importance. The unavailability of blood and related constituents, such as plasma, red blood cells and platelets, may cause several complications and even be fatal for some patients. This problem further gets amplified, especially in emergency situations accompanied by disruptions in the road-based logistics infrastructure, as the demand for emergency blood packets surges suddenly. This paper models a drone-based last-mile delivery system for blood supply chains. The optimisation model deals with the distribution of blood to various hospitals while minimising the total demand-distance pair under distance and payload constraints. Further, the evolved mixed integer linear programming (MILP) model demonstrates multiple real-world scenarios. A comparison of the time efficiency and cost of traditional road-based logistics vis-à-vis a drone-based system to deliver blood packets is also shown. Several implications for researchers, logistics companies and experts working on drone-based logistics are also derived.", "keywords": [ "Health care", "Healthcare delivery", "Healthcare system", "Delivery system" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/13675567.2025.2549129" }, { "id": "https://openalex.org/W4393121483", "doi": "10.1007/978-3-031-51997-0_24", "title": "Last-Mile Delivery Innovations: The Future of E-commerce Logistics", "year": 2024, "publication_date": "2024-01-01", "type": "book-chapter", "language": "en", "authors": [ "C. Nagadeepa", "Berenika Dyczek", "Ar. Keerti Mishra", "Валерій Михайлович Бондаренко", "Oleksandr Omelianenko", "Kateryna Sokoliuk" ], "first_author": "C. Nagadeepa", "venue": "Studies in systems, decision and control", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Last mile (transportation)", "E-commerce", "Mile", "Business", "Computer science", "World Wide Web", "Geography" ], "cited_by_count": 13, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-51997-0_24" }, { "id": "https://openalex.org/W4391646061", "doi": "10.59478/atct.2023.8", "title": "Study of barriers for the use of drones in the last mile logistics", "year": 2023, "publication_date": "2023-01-01", "type": "conference-paper", "language": "en", "authors": [ "Snežana Radoman Tadić", "Ljubica Radovanović", "Mladen Dragan Krstić", "Miloš Veljović" ], "first_author": "Snežana Radoman Tadić", "venue": null, "publisher": null, "abstract": "Effective last mile (LM) delivery is critical to efficient functioning of supply chains.In addition to speed and cost of delivery, environmental and social sustainability are increasingly important factors in last mile logistics (LML), especially in urban areas.Sustainable solutions involve application of various modern technologies.Autonomous vehicles and drones have attracted special attention of researchers in recent years, with their vast application potential.Despite potential benefits of deployment in LML, future of drone logistics is uncertain due to a number of barriers.Aim of this study is barriers analysis, evaluation and ranking, to identify those that prevent wider application of drones in LM to the greatest extent.For solving the defined problem this study used the fuzzy Delphi ANP (fuzzy DANP).Results indicate that the most critical barriers to implementation are lack of regulations, drone tracking, drone owners' liability and obstacle and collision avoidance.Higher perceived risk and short flight range are of lesser impact.The contribution of this study is in the fact that the analysis of barriers to the implementation of drones is assessed from different perspectives and interests of different stakeholders, which represents a new approach compared to previous research in this field.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Business", "Computer science", "Aeronautics", "Engineering", "Geography" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.atct.ba/conference-proceedings/2023/8-study-of-barriers-for-the-use-of-drones-in-the-last-mile-logistics.pdf" }, { "id": "https://openalex.org/W2793389968", "doi": "10.15722/jds.16.2.201802.19", "title": "Heuristic Method for Collaborative Parcel Delivery with Drone", "year": 2018, "publication_date": "2018-02-01", "type": "article", "language": "en", "authors": [ "Jibok Chung" ], "first_author": "Jibok Chung", "venue": "Journal of Distribution Science", "publisher": "Korea Distribution Science Association", "abstract": "Purpose – Drone delivery is expected to revolutionize the supply chain industry. This paper aims to introduce a collaborative parcel...", "keywords": [ "Drone", "Heuristic", "Computer science", "Business", "Operations research", "Psychology", "Artificial intelligence", "Engineering", "Biology" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.15722/jds.16.2.201802.19" }, { "id": "https://openalex.org/W4406064197", "doi": "10.1016/j.trc.2024.104986", "title": "Near time-optimal trajectory optimisation for drones in last-mile delivery using spatial reformulation approach", "year": 2025, "publication_date": "2025-01-04", "type": "article", "language": "en", "authors": [ "Y.Y. Chan", "Kam K.H. Ng", "Tianqi Wang", "K. K. Hon", "Chun-Ho Liu" ], "first_author": "Y.Y. Chan", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Mile", "Trajectory", "Computer science", "Transport engineering", "Last mile (transportation)", "Engineering", "Aeronautics", "Operations research", "Geography", "Geodesy" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2024.104986" }, { "id": "https://openalex.org/W2774532011", "doi": "10.1109/soli.2017.8120986", "title": "Post-production analysis approach for drone delivery fleet", "year": 2017, "publication_date": "2017-09-01", "type": "conference-paper", "language": "en", "authors": [ "Asma Troudi", "Sid-Ali Addouche", "Sofiène Dellagi", "Abderrahman El Mhamedi" ], "first_author": "Asma Troudi", "venue": null, "publisher": null, "abstract": "This paper treats a drone delivery parcel's problematic in an urban area. The civil application of drone has been developed during these last decades especially drone delivery applications. In this paper, we focus on drone delivery application in the urban area for last-mile parcel delivery. The new issue is not only the drone design but also the logistics support of a massive fleet of drones with a mission to deliver parcels in a dense urban area. We hereby treat problematic by focusing on Logistics Support System. In this context, the commercialized drone is a considered as a system on the shelf. we propose a Post-Production Logistics Support Analysis to cover the exploitation phase of a drone delivery operator.", "keywords": [ "Drone", "Context (archaeology)", "Last mile (transportation)", "Computer science", "City logistics", "Aeronautics", "Transport engineering", "Engineering", "Mile", "Geography" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/soli.2017.8120986" }, { "id": "https://openalex.org/W4313593567", "doi": "10.1016/j.trb.2022.12.007", "title": "Exact solution approaches for the minimum total cost traveling salesman problem with multiple drones", "year": 2023, "publication_date": "2023-01-04", "type": "article", "language": "en", "authors": [ "Gizem Özbaygın Tiniç", "Oya Ekin Karaşan", "Bahar Y. Kara", "James F. Campbell", "Aysu Ozel" ], "first_author": "Gizem Özbaygın Tiniç", "venue": "Transportation Research Part B Methodological", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Travelling salesman problem", "Drone", "Mathematical optimization", "Traveling purchaser problem", "2-opt", "Mathematics", "Computer science", "Biology" ], "cited_by_count": 71, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trb.2022.12.007" }, { "id": "https://openalex.org/W4312851655", "doi": "10.51680/ev.35.2.8", "title": "Drone last mile delivery: An assessment of the viable market and security potential of drone delivery", "year": 2022, "publication_date": "2022-01-01", "type": "article", "language": "en", "authors": [ "Igor Grofelnik", "Uroš Godnov", "Marjan Sternad" ], "first_author": "Igor Grofelnik", "venue": "Ekonomski vjesnik", "publisher": "Faculty of Economics, University of Osijek", "abstract": "Purpose: the paper includes a review of the literature in the field of drones, drone technology, possible implementation in the field of the last mile concept, legislation, suitability of technology in the field of security, weather conditions, social acceptance and later focuses on checking the possible implementation of drones according to the set parameters. Methodology: for the purposes of research and obtaining answers to the posed research question and hypotheses, we used the method of literature review in the selected field, panel data analysis, conducted interviews with experts in the field of delivery drones in the Republic of Slovenia, and conducted secondary research. Results: the results show an assessment of the possible implementation of drones based on the analysis of the obtained data and interviews. We determined a realistic assessment of the potential of delivery drones, in which we included several vital aspects necessary for implementation. Conclusion: it was found that the current technology is not yet fully adequate, and significant technological improvements are also needed. It is also necessary to plan integrated urban spatial solutions that will enable safe and efficient delivery in the supply chain. Namely, delivery with drones is currently ineffective due to flight safety, harmful sound emissions and the inability to fly in bad weather conditions. Based on a literature review and a survey among large logistics companies, it was found that there are still many barriers to implementation due to legal norms and regulations, which are currently very constructive. It is unlikely, however, that parcel delivery will take off in an urban environment soon, as there are still many unknowns. With proper planning and use of suburban consolidation centres, e-vans, e-cars and bicycles are currently economically viable for last mile delivery.", "keywords": [ "Drone", "Field (mathematics)", "Legislation", "Delivery Performance", "Business", "Plan (archaeology)", "Risk analysis (engineering)", "Computer science", "Computer security", "Process management", "Political science", "Geography" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hrcak.srce.hr/ojs/index.php/ekonomski-vjesnik/article/download/24683/13067" }, { "id": "https://openalex.org/W4411842761", "doi": "10.55121/tdr.v3i1.449", "title": "Integrating 5PL Frameworks with Drone-Based Last-Mile Delivery: A Model for Future-Ready Logistics", "year": 2025, "publication_date": "2025-06-29", "type": "article", "language": "en", "authors": [ "Tejinder Singh Lakhwani" ], "first_author": "Tejinder Singh Lakhwani", "venue": "Transportation Development Research", "publisher": null, "abstract": "The rapid evolution of logistics service providers from 1PL to 5PL has underscored the growing need for intelligent, data-driven orchestration across the supply chain. Simultaneously, drone-based delivery has emerged as a promising solution to last-mile challenges, particularly in urban congestion zones and infrastructure-deficient rural areas. However, current deployments of drone logistics remain largely siloed and unintegrated with broader digital logistics platforms. This paper proposes a novel conceptual framework that embeds drone-based last-mile delivery within the orchestration architecture of fifth-party logistics (5PL) systems. Leveraging a multi-agent digital twin model, the study integrates technologies such as IoT for real-time tracking, AI-based metaheuristics (ALNS, PSO, NSGA-II) for route and hub optimization, and blockchain for SLA compliance. A simulation case based on India’s rural healthcare supply chain and ONDC clusters demonstrates substantial improvements in delivery time (↓65%), operational cost (↓40%), and carbon footprint (↓90%) over conventional 4PL systems. Sensitivity analyses under weather fluctuations, demand surges, and battery degradation validate the model’s resilience and adaptability. The findings position 5PLs as future-ready orchestrators of autonomous delivery systems and offer actionable insights for policymakers, supply chain managers, and technology developers toward building sustainable and scalable drone logistics ecosystems.The framework emphasizes interoperability and modular deployment, ensuring ease of integration with evolving logistics platforms.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "City logistics", "Computer science", "Business", "Engineering", "Transport engineering", "Geography" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.55121/tdr.v3i1.449" }, { "id": "https://openalex.org/W4382584167", "doi": "10.1016/j.aei.2023.102071", "title": "The time-dependent electric vehicle routing problem with drone and synchronized mobile battery swapping", "year": 2023, "publication_date": "2023-06-28", "type": "article", "language": "en", "authors": [ "Xiaoxue Ren", "Houming Fan", "Houming Fan", "Ming-Xin Bao", "Hao Fan", "Hao Fan" ], "first_author": "Xiaoxue Ren", "venue": "Advanced Engineering Informatics", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Battery (electricity)", "Lagrangian relaxation", "Computer science", "Charging station", "Electric vehicle", "Energy consumption", "Real-time computing", "Engineering", "Automotive engineering", "Mathematical optimization", "Electrical engineering" ], "cited_by_count": 51, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.aei.2023.102071" }, { "id": "https://openalex.org/W2889762228", "doi": "10.15826/recon.2018.4.2.008", "title": "Drone technology for last-mile delivery in Russia: a tool to develop local markets", "year": 2018, "publication_date": "2018-06-30", "type": "article", "language": "en", "authors": [ "Haula Kitonsa" ], "first_author": "Haula Kitonsa", "venue": "R-Economy", "publisher": "Ural Federal University", "abstract": "As the popularity of online shopping increases, last-mile delivery is gaining more and more attention of e-commerce companies. One of the viable solutions to maximizing the benefits of such delivery and cutting its costs is the usage of the rapidly developing drone technology. However, drone delivery is associated with a number of safety and privacy, which makes legislators uneasy about permitting the commercial use of drones. In this paper, we compare the drone regulations applied in various countries with those of Russia and analyze the criteria used to develop such regulations. Six general approaches are thus outlined: officially banning commercial drone operation; making it virtually impossible for drone operators to acquire the necessary registration and license; allowing to fly drones in exceptional cases over restricted areas; prohibiting to fly drones beyond the pilot’s line of visual sight; allowing to fly drones if standard requirements are met; and, finally, following the substantial precedent principle. This analysis shows us the possible strategies Russia could adopt to regulate commercial drone usage. It is thus suggested that Russia should follow the example of Rwanda and China and allow to experiment with drone delivery in rural areas, where the risk to people’s lives and property in case of drone malfunction are lower than in urban areas.", "keywords": [ "Drone", "License", "Popularity", "Business", "Last mile (transportation)", "China", "Computer security", "Mile", "Computer science", "Geography", "Law", "Political science" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "http://r-economy.ru/wp-content/uploads/2018/06/r-economy_2018_v4_2_03.pdf" }, { "id": "https://openalex.org/W2889295151", "doi": "10.1007/978-3-030-00111-7_10", "title": "Developing a Distributed Drone Delivery System with a Hybrid Behavior Planning System", "year": 2018, "publication_date": "2018-01-01", "type": "conference-paper", "language": "en", "authors": [ "Daniel G. Krakowczyk", "Jannik Wolff", "Alexandru Ciobanu", "Dennis Julian Meyer", "Christopher-Eyk Hrabia" ], "first_author": "Daniel G. Krakowczyk", "venue": "Lecture notes in computer science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Computer science", "Drone", "Simulation" ], "cited_by_count": 13, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-030-00111-7_10" }, { "id": "https://openalex.org/W4225678912", "doi": "10.2139/ssrn.4080821", "title": "Collaborative Truck Multi-Drone Delivery System Considering Drone Scheduling and En-Route Operations", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Teena Thomas", "Sharan Srinivas", "Chandrasekharan Rajendran" ], "first_author": "Teena Thomas", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Scheduling (production processes)", "Aeronautics", "Computer science", "Engineering", "Transport engineering", "Operations management", "Aerospace engineering" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4080821" }, { "id": "https://openalex.org/W3188450829", "doi": "10.1016/j.comcom.2021.07.013", "title": "Traveling salesman problem with drone under recharging policy", "year": 2021, "publication_date": "2021-07-20", "type": "article", "language": "en", "authors": [ "Emine Eş Yürek", "H. Cenk Özmutlu" ], "first_author": "Emine Eş Yürek", "venue": "Computer Communications", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Computer science", "Truck", "Battery (electricity)", "2-opt", "Heuristic", "Bottleneck traveling salesman problem", "Mathematical optimization", "Operations research", "Algorithm", "Artificial intelligence" ], "cited_by_count": 38, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.comcom.2021.07.013" }, { "id": "https://openalex.org/W4388766824", "doi": "10.1016/j.eswa.2023.122483", "title": "Multi-Depot Vehicle Routing Problem with Drones: Mathematical formulation, solution algorithm and experiments", "year": 2023, "publication_date": "2023-11-17", "type": "article", "language": "en", "authors": [ "Petr Stodola", "Libor Kutěj" ], "first_author": "Petr Stodola", "venue": "Expert Systems with Applications", "publisher": "Elsevier BV", "abstract": "The use of Unmanned Aerial Vehicles (UAVs) is expected to grow rapidly in the coming years, driven by technological advancements, cost-effectiveness, and the increasing demand for faster and more efficient delivery solutions. This article deals with the mathematical formulation of the Multi-Depot Vehicle Routing Problem with Drones (MDVRP-D), whereby a set of heterogeneous trucks, each paired with a UAV, are located in different depots. Both types of vehicles deliver goods to customers; UAVs are dispatched from trucks while en route to make the last-mile delivery. A metaheuristic algorithm based on the Ant Colony Optimization (ACO) principle is proposed as the solution. This algorithm has been adapted for this newly proposed problem; the novel mechanics include the probabilistic decision to dispatch an UAV, the selection of a customer to be served, and local search optimization. Extensive computational experiments are performed to verify the proposed algorithm. First, its performance is compared with Adaptive Large Neighborhood Search (ALNS) metaheuristics on a set of Vehicle Routing Problem with Drones (VRP-D) benchmarks. A set of various benchmark instances are subsequently proposed for the newly formulated MDVRP-D (differing in complexity and graph topology). Finally, the behavior of the proposed algorithm is thoroughly analyzed, especially in respect of features connected with UAVs. The findings presented in this article provide valuable contributions to the NP-hard models related to the Travelling Salesman Problem (TSP) and to the very popular ACO-based algorithms.", "keywords": [ "Vehicle routing problem", "Computer science", "Travelling salesman problem", "Ant colony optimization algorithms", "Metaheuristic", "Mathematical optimization", "Drone", "Benchmark (surveying)", "Truck", "Set (abstract data type)", "Algorithm", "Probabilistic logic" ], "cited_by_count": 47, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.eswa.2023.122483" }, { "id": "https://openalex.org/W4392015111", "doi": "10.1145/3649224", "title": "UAV-Based Delivery Systems: A Systematic Review, Current Trends, and Research Challenges", "year": 2024, "publication_date": "2024-02-21", "type": "review", "language": "en", "authors": [ "Francesco Betti Sorbelli" ], "first_author": "Francesco Betti Sorbelli", "venue": "ACM Journal on Autonomous Transportation Systems", "publisher": "Association for Computing Machinery", "abstract": "The rising popularity of drones significantly impacts package delivery services, offering both unique opportunities and challenges. This survey explores the diverse applications of drones for last-mile deliveries, highlighting their capacity to access remote areas and create new business prospects. Use cases, ranging from critical medical deliveries to addressing COVID-19 pandemic needs, underscore the transformative potential of drone technology. While recognizing drones’ eco-friendly attributes in eliminating harmful gas emissions, the survey addresses battery constraints, necessitating an investigation into physical energy models to extend flight autonomy. This becomes crucial for operational capabilities, especially in adverse weather conditions. A reliable communication infrastructure is crucial for the success of drone operations in package delivery, especially during unexpected events, as seamless connectivity plays a key role in facilitating efficient control and monitoring between ground stations and drones. This enables dynamic rerouting, enhancing overall delivery reliability. The survey explores innovative approaches, including collaborations with other vehicles like trucks, trains, and buses, optimizing the last-mile delivery process. Despite the transformative potential, concerns about privacy, security, safety, and risk management in drone delivery are acknowledged. The work also emphasizes responsible and ethical implementation, considering diverse concerns associated with widespread adoption. In contrast to existing survey articles focused on specific technical aspects, this comprehensive survey broadens its scope. It covers ethical issues, sustainability aspects, healthcare systems, physics models, innovative approaches, reliable communications, security and safety concerns, and real test-beds in drone-based delivery systems. The survey not only identifies potential applications and tackles technical challenges but also integrates broader considerations. In addition, this work extensively explores the motivations, lessons learned, and future directions in the realm of drone delivery. Analyzing existing literature, it provides valuable insights for researchers, industry professionals, policymakers, and stakeholders keen on understanding the dynamic evolution of drone technology in the package delivery domain.", "keywords": [ "Drone", "Risk analysis (engineering)", "Process (computing)", "Computer science", "Computer security", "Engineering", "Business" ], "cited_by_count": 117, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1145/3649224" }, { "id": "https://openalex.org/W4415684823", "doi": "10.3390/aerospace12110967", "title": "A Scheduling Model for Optimizing Joint UAV-Truck Operations in Last-Mile Logistics Distribution", "year": 2025, "publication_date": "2025-10-29", "type": "article", "language": "en", "authors": [ "Xiaocheng Liu", "Yuhan Wang", "Meilong Le", "Zhongye Wang", "Honghai Zhang" ], "first_author": "Xiaocheng Liu", "venue": "Aerospace", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "This paper investigates the joint scheduling problem of unmanned aerial vehicles (UAVs) and trucks for community logistics, where UAVs act as service providers for last-mile delivery and trucks serve as mobile storage platforms for drone deployment. To address the complexity of decision variables, this paper proposes a three-stage solution scheme that divides the problem into the following: (1) UAV mission set generation via clustering, (2) truck-drone route planning, and (3) collaborative scheduling via a Mixed-Integer Linear Programming (MILP) model. The MILP model, solved exactly using Gurobi, optimizes truck movements and drone operations to minimize total delivery time, representing the core contribution. In the experimental section, to verify the correctness and effectiveness of the proposed Mixed-Integer Linear Programming (MILP) model, comparative experiments were conducted against a heuristic algorithm based on empirical intuitive decision-making. The solution results of experiments with different scales indicate that the joint scheduling model outperforms the scheduling strategies based on empirical experience across various scenario sizes. Additionally, multiple experiments conducted under different parameter settings within the same scenario successfully demonstrated that the model can stably be solved without deteriorating results when parameters change. Furthermore, this study observed that the relationship between the increase in the number of drones and the decrease in the total consumed time is not a simple linear relationship. This phenomenon is speculated to be due to the periodic patterns exhibited by the drone scheduling sequence, which align with the average duration of individual tasks.", "keywords": [ "Scheduling (production processes)", "Drone", "Correctness", "Linear programming", "Job shop scheduling", "Truck" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2226-4310/12/11/967/pdf?version=1761751548" }, { "id": "https://openalex.org/W4398225846", "doi": "10.1007/978-3-031-60603-8_27", "title": "Online Drone Scheduling for Last-Mile Delivery", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Saswata Jana", "Giuseppe Francesco Italiano", "Manas Jyoti Kashyop", "Athanasios L. Konstantinidis", "Evangelos Kosinas", "Partha Sarathi Mandal" ], "first_author": "Saswata Jana", "venue": "Lecture notes in computer science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Computer science", "Mile", "Last mile (transportation)", "Scheduling (production processes)", "Operations management", "Engineering", "Geography" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-031-60603-8_27" }, { "id": "https://openalex.org/W3112718299", "doi": "10.1007/978-3-030-64843-5_9", "title": "Energy-Constrained Drone Delivery Scheduling", "year": 2020, "publication_date": "2020-01-01", "type": "conference-paper", "language": "en", "authors": [ "Rafael Papa", "Ionut Cardei", "Mihaela Cardei" ], "first_author": "Rafael Papa", "venue": "Lecture notes in computer science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Computer science", "Scheduling (production processes)", "Scalability", "Operations research", "Job shop scheduling", "Distributed computing", "Real-time computing", "Mathematical optimization", "Computer network", "Database", "Engineering" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-030-64843-5_9" }, { "id": "https://openalex.org/W4399403852", "doi": "10.1109/tetci.2024.3406689", "title": "Transfer Optimization for Heterogeneous Drone Delivery and Pickup Problem", "year": 2024, "publication_date": "2024-06-06", "type": "article", "language": "en", "authors": [ "Xupeng Wen", "Guohua Wu", "Jiao Liu", "Yew-Soon Ong" ], "first_author": "Xupeng Wen", "venue": "IEEE Transactions on Emerging Topics in Computational Intelligence", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Recently, with the enhancement of drone's payload and endurance capability, drone logistics has received extensive attention from giant logistics enterprises. This research delves into the Heterogeneous multi-Drone Delivery Pickup Problem (HDDPP) through a novel distribution mode. Here, a large drone ferries multiple smaller drones to a specified sub-region. These smaller drones oversee parcel delivery and pickup tasks before returning to automated airports for recycling. Then we formulate it into an open two-echelon multi-objective routing optimization problem, addressing pickup and delivery problems. To enhance optimization efficiency, relying on conventional optimization algorithms initiates the optimization process from an initial state, neglecting pertinent empirical knowledge embedded in optimized instances. This oversight results in a considerable squandering of computational resources. Based on the above motivation, we propose a Transfer Optimization with Heuristic Operators (TOHO) method. TOHO adopts insights from previously optimized task models, ensuring quick convergence for new tasks. We also present a mapping method rooted in topological alignment, enabling effective alignment between source and target instances, which fosters faster optimization convergence. Furthermore, we design a voting-mechanism-based ensemble genetic optimization strategy employing heuristic operators to select the Pareto frontier with high-quality diversity and convergence. Extensive experimental results on extended benchmark instances validate the efficacy of TOHO, and underscore its capability to speed up the optimization while ensuring superior knowledge transfer compared to baselines.", "keywords": [ "Pickup", "Drone", "Computer science", "Artificial intelligence", "Biology" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tetci.2024.3406689" }, { "id": "https://openalex.org/W4405107620", "doi": "10.1080/23249935.2024.2435977", "title": "An optimisation model of hierarchical facility location problem for urban last-mile delivery with drones", "year": 2024, "publication_date": "2024-12-06", "type": "article", "language": "en", "authors": [ "Guangyuan Zhang", "Jianping Zhang", "Bisheng He", "Ruiqing Zhang", "Xiang Zou" ], "first_author": "Guangyuan Zhang", "venue": "Transportmetrica A Transport Science", "publisher": "Taylor & Francis", "abstract": "Drones have, in recent years, been considered as a promising way for the last-mile delivery of urban logistics. In view of limited or short battery life of drones in every operation, the drone recharging stations and their locations are crucial to ensure delivery accessibility and to accomplish the required mission. Therefore, in addition to considering the selection of service centres and demand nodes, the location of recharging stations should also be incorporated into the proposed model of hierarchical facility location problem (HFLP). Many existing researches on drone recharging station locations assume that the delivery demand is known and only a single path is designed to meet the demand by using queuing theory models to describe node-based service waiting time. However, the reality is that we are still in the infrastructure planning stage for drone delivery, in which the demand is unknown in most cases. Our research proposes a novel mix-integer programming model to solve the HFLP for the last-mile drone delivery in urban areas, aiming to minimise the deployment, operation, and maintenance (DOM) costs of recharging stations, service centres, and paths. We have also incorporated a demand satisfaction constraint into the selection of effective alternative paths that meet the delivery accessibility. On the other hand, a sensitivity analysis in our study reveals varying degrees of impact on DOM costs and effective alternative path quantities, whose results would be useful to practical drone logistics delivery in urban areas.", "keywords": [ "Drone", "Last mile (transportation)", "Computer science", "Operations research", "Service (business)", "Facility location problem", "Queueing theory", "Transport engineering", "Computer network", "Mile", "Engineering", "Business" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/23249935.2024.2435977" }, { "id": "https://openalex.org/W3214725302", "doi": "10.1016/j.cie.2021.107784", "title": "Drone scheduling model for delivering small parcels to remote islands considering wind direction and speed", "year": 2021, "publication_date": "2021-11-11", "type": "article", "language": "en", "authors": [ "Hosang Jung", "Junsu Kim" ], "first_author": "Hosang Jung", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Scheduling (production processes)", "Computer science", "Wind speed", "Sensitivity (control systems)", "Real-time computing", "Simulation", "Environmental science", "Marine engineering", "Meteorology", "Engineering", "Geography" ], "cited_by_count": 56, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2021.107784" }, { "id": "https://openalex.org/W4416074900", "doi": "10.3390/drones9110782", "title": "Resilient Last-Mile Logistics in Smart Cities Through Multi-Visit and Time-Dependent Drone–Truck Collaboration", "year": 2025, "publication_date": "2025-11-10", "type": "article", "language": "en", "authors": [ "Qinxin Xiao", "Jiaojiao Gao" ], "first_author": "Qinxin Xiao", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Urban logistics in smart cities are increasingly challenged by congestion, sustainability pressures, and the growing demand for resilient delivery systems. To address these challenges, this study introduces the Multi-Visit Time-Dependent Truck–Drone Routing Problem with simultaneous Pickup and Delivery (MTTRP-PD), a novel framework that integrates three realistic features: (i) drones serving multiple customers per sortie, (ii) time-dependent truck speeds reflecting dynamic traffic conditions, and (iii) synchronized pickup and delivery between trucks and drones. By incorporating these elements, the proposed model provides a more realistic and comprehensive representation of urban air-ground collaborative logistics in the last mile. An optimization framework and an efficient solution approach are developed and validated through computational experiments. The results demonstrate that enabling multi-visit sortie and simultaneous pickup–delivery operations can significantly reduce logistics costs compared with conventional single-visit or delivery-only strategies. Sensitivity analyses further reveal the critical influence of dynamic traffic conditions on fleet configuration and operational decision making. The findings offer actionable insights for logistics operators and policymakers, illustrating how coordinated UAV–truck collaboration can enhance efficiency, resilience, and environmental sustainability in next-generation urban logistics systems.", "keywords": [ "Truck", "Sustainability", "Drone", "City logistics", "Supply chain", "Vehicle routing problem", "Routing (electronic design automation)", "Humanitarian Logistics" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/9/11/782/pdf?version=1762786573" }, { "id": "https://openalex.org/W4376456745", "doi": "10.1109/tits.2023.3271430", "title": "Logistics in the Sky: A Two-Phase Optimization Approach for the Drone Package Pickup and Delivery System", "year": 2023, "publication_date": "2023-05-11", "type": "article", "language": "en", "authors": [ "Fangyu Hong", "Guohua Wu", "Qizhang Luo", "Huan Liu", "Xiaoping Fang", "Witold Pedrycz" ], "first_author": "Fangyu Hong", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The application of drones in last-mile distribution has been a contentious research topic in recent years. Existing urban distribution modes mostly depend on trucks. This paper proposes a novel package pickup and delivery mode and system wherein multiple drones collaborate with automatic devices. The proposed mode uses free areas on top of residential buildings to set automatic devices as delivery and pickup points of packages, and employs drones to transport packages between buildings and depots. The integrated scheduling problem of package drop-pickup considering${m}$-drones,${m}$-depots, and${m}$-customers is crucial for the system. Therefore, we propose a simulated-annealing-based two-phase optimization (SATO) approach to solve this problem. In the first phase, tasks are allocated to depots for serving, such that the initial problem is decomposed into multiple single-depot scheduling problems with${m}$-drone. In the second phase, considering the drone capability and task demand constraints, we generated a route-planning scheme for drones in each depot. Concurrently, an improved variable neighborhood descent (IVND) algorithm was designed in the first phase to reallocate tasks, and a local search (LS) algorithm was proposed to search for high-quality solutions in the second phase. Finally, extensive experiments and comparative studies were conducted to verify the effectiveness of the proposed approach.", "keywords": [ "Drone", "Notation", "Pickup", "Simulated annealing", "Computer science", "Mathematics", "Algorithm", "Artificial intelligence", "Arithmetic" ], "cited_by_count": 64, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2023.3271430" }, { "id": "https://openalex.org/W3196669242", "doi": "10.1016/j.trpro.2021.07.012", "title": "Ensuring the logistics of the last mile from the perspective of distribution companies", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Peter Jucha", "Tatiana Čorejová" ], "first_author": "Peter Jucha", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "In recent years, last mile logistics has been a serious issue, mainly because customers expect fast and reliable delivery of their order, no matter where they buy it or order it. Distribution companies are forced to develop innovative solutions for the delivery of goods to customers to meet their needs and meet their requirements. In the world, drones or autonomous vehicles, for example, are already used to deliver certain types of goods within the last mile, but in most cases traditional methods such as postal and courier services are used to deliver goods. The aim of the article is to state the possibilities of delivery of goods to customers, which are currently offered by distribution companies in Slovakia. For this purpose, the individual methods of delivery of goods, which are offered to customers by distribution companies and e-shops, were compared, evaluated in terms of their positive and negative aspects. Subsequently, the methods of delivery of goods in relation to the type of goods and customer requirements were investigated. The most frequently offered ways of delivering goods to customers are delivery of goods to a stone shop or a post office. On the other hand, the least offered option is the delivery of goods to an external dispensing point.", "keywords": [ "Last mile (transportation)", "Order (exchange)", "Business", "Mile", "Distribution (mathematics)", "Marketing", "Goods and services", "Finished good", "Point (geometry)", "Operations management", "Commerce", "Engineering" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2352146521004075/pdf" }, { "id": "https://openalex.org/W4402484891", "doi": "10.3390/drones8090477", "title": "Intelligent Parcel Delivery Scheduling Using Truck-Drones to Cut down Time and Cost", "year": 2024, "publication_date": "2024-09-12", "type": "article", "language": "en", "authors": [ "Tamer Ahmed Farrag", "Heba Askr", "Mostafa A. Elhosseini", "Aboul Ella Hassanien", "Mai A. Farag" ], "first_author": "Tamer Ahmed Farrag", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "In the evolving landscape of logistics, drone technology presents a solution to the challenges posed by traditional ground-based deliveries, such as traffic congestion and unforeseen road closures. This research addresses the Truck–Drone Delivery Problem (TDDP), wherein a truck collaborates with a drone, acting as a mobile charging and storage unit. Although the Traveling Salesman Problem (TSP) can represent the TDDP, it becomes computationally burdensome when nodes are dynamically altered. Motivated by this limitation, our study’s primary objective is to devise a model that ensures swift execution without compromising the solution quality. We introduce two meta-heuristics: the Strawberry Plant, which refines the initial truck schedule, and Genetic Algorithms, which optimize the combined truck–drone schedule. Using “Dataset 1” and comparing with the Multi-Start Tabu Search (MSTS) algorithm, our model targeted costs to remain within 10% of the optimum and aimed for a 73% reduction in the execution time. Of the 45 evaluations, 37 met these cost parameters, with our model surpassing MSTS in eight scenarios. In contrast, using “Dataset 2” against the CPLEX solver, our model optimally addressed all 810 experiments, while CPLEX managed only 90 within the prescribed time. For 20-customer scenarios and more, CPLEX encountered memory limitations. Notably, when both methods achieved optimal outcomes, our model’s computational efficiency exceeded CPLEX by a significant margin. As the customer count increased, so did computational challenges, indicating the importance of refining our model’s strategies. Overall, these findings underscore our model’s superiority over established solvers like CPLEX and the economic advantages of drone-assisted delivery systems.", "keywords": [ "Computer science", "Drone", "Truck", "Travelling salesman problem", "Heuristics", "Solver", "Schedule", "Tabu search", "Scheduling (production processes)", "Genetic algorithm", "Job shop scheduling", "Operations research" ], "cited_by_count": 15, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/8/9/477/pdf?version=1726138337" }, { "id": "https://openalex.org/W2982078879", "doi": "10.1109/vnc48660.2019.9062772", "title": "Unmanned Aerial Vehicles in Logistics: Efficiency Gains and Communication Performance of Hybrid Combinations of Ground and Aerial Vehicles", "year": 2019, "publication_date": "2019-12-01", "type": "conference-paper", "language": "en", "authors": [ "Manuel Patchou", "Benjamin Sliwa", "Christian Wietfeld" ], "first_author": "Manuel Patchou", "venue": null, "publisher": null, "abstract": "Unmanned Aerial Vehicles (UAVs) have drastically gained popularity in various Intelligent Transportation System (ITS) applications to improve the safety and efficiency of transportation systems. In this context, the combination of ground vehicles, such as delivery trucks, with drones to assist in the last-mile pick-up and delivery of the parcels has been recently proposed. While aerial vehicles promise increased efficiency based on flexible routes and parallelized operation, highly reliable wireless communication is also required for the control and coordination of potentially many drones acting in a self-organized way. In this paper, we analyze the improvements procured by drone usage in parcel delivery compared to traditional delivery and propose a simulation framework to further quantify the efficiency gains of the parcel delivery logistics and to analyze the performance of different wireless communications options. To this end, we consider a heterogeneous vehicle routing problem with various constraints. We consider two approaches regarding the dispatching and recovery of drones and evaluate their benefits as opposed to parcel delivery with a classic truck only. Furthermore, we compare two networking technologies for enabling coordination of the self-organizing teams of drones with a realistically modeled environment: one approach relying on base station oriented Long Term Evolution (LTE) vs. a more decentralized Cellular Vehicle-to-Everything (C-V2X) solution. The results show time savings of nearly 80% can be achieved through drone usage and that the negative impact of urban shadowing on network communications in the base station oriented LTE approach can be compensated by leveraging decentralized C-V2X communications.", "keywords": [ "Drone", "Base station", "Truck", "Computer science", "Context (archaeology)", "Wireless", "Popularity", "Computer network", "Last mile (transportation)", "Transport engineering", "Distributed computing", "Telecommunications" ], "cited_by_count": 25, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1910.10451" }, { "id": "https://openalex.org/W3110904867", "doi": "10.1109/ieeecloudsummit48914.2020.00024", "title": "An IoT based Three-Dimensional Dynamic Drone Delivery (3D4) System", "year": 2020, "publication_date": "2020-10-01", "type": "conference-paper", "language": "en", "authors": [ "Sreenivas Eeshwaroju", "Praveena Jakkula", "Iheb Abdellatif" ], "first_author": "Sreenivas Eeshwaroju", "venue": null, "publisher": null, "abstract": "The next decades will witness a huge growth of cities whether from a population or an infrastructure standpoint. Consequently, services like last-mile delivery will be harder to manage and operate due to the complex city ecosystem (people, infrastructure, and services). Due to the increase in population, more high-rise buildings will be seen in cities. In addition, the rapid growth in information and communication technology will require smart ways to meet the delivery needs of people. This paper proposes a “Three-Dimensional Dynamic Drone Delivery (3D4)” system that aims to enable vertical deliveries by adding an extra dimension (Z-axis) to the conventional two-dimensional delivery systems. The proposed system enables the user to receive shipment anywhere as requested. This system also addresses common delivery problems such as conventional fixed-point deliveries, package security, and enhance customer satisfaction.", "keywords": [ "Drone", "Last mile (transportation)", "Internet of Things", "Computer science", "Witness", "Population", "Computer security", "Dimension (graph theory)", "Telecommunications", "Mile", "Geography" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/ieeecloudsummit48914.2020.00024" }, { "id": "https://openalex.org/W3204412432", "doi": "10.1109/asiancon51346.2021.9545035", "title": "Feasibility of Multi-Configuration Unmanned Aerial Vehicle for Last Mile Delivery of Medical Supplies", "year": 2021, "publication_date": "2021-08-27", "type": "conference-paper", "language": "en", "authors": [ "Vamsi krishna Varigonda", "Advait Borole", "Ajay Hudge", "Chitransh Yadav", "Vinoth Kumar Annamalai" ], "first_author": "Vamsi krishna Varigonda", "venue": "2021 Asian Conference on Innovation in Technology (ASIANCON)", "publisher": null, "abstract": "Access to critical medicines is hindered throughout the world due to inadequate transportation, communication, or supply chain infrastructure. Numerous immunization programs in underdeveloped and developing countries face countless challenges in getting life-saving vaccines to those who need them the most. During the Covid-19 period, the shortcomings of the medical supply chain and delivery system were evident. Unmanned aerial vehicles play a vital role in delivering medical supplies; however, conventional multi-rotors have a limited flight time, which defines the range of the missions, whereas a plane has the capability of conducting long-range missions. Shortcomings of using planes for the operation is the need for a runway, limiting its reach in an urban environment due to the unavailability of space. We are proposing a multi-configuration unmanned aerial vehicle for medical supplies delivery. It is also referred to as Vertical takeoff and landing (VTOL), which can take off, and land without the need for the runway. Furthermore has extended operational range compared to the multi-rotors given its functional behavior as a plane. We have emulated aerial vehicles' configurations with real-life mission parameters and compared them with our proposed Unmanned aerial vehicles model. The design, fabrication process of the multi-configuration unmanned aerial vehicle for the medical supplies delivery is explained in detail in this paper.", "keywords": [ "Unavailability", "Runway", "Last mile (transportation)", "Aeronautics", "Takeoff and landing", "Takeoff", "Computer science", "Drone", "Range (aeronautics)", "Transport engineering", "Aerospace engineering", "Engineering" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/asiancon51346.2021.9545035" }, { "id": "https://openalex.org/W2995169442", "doi": "10.1109/access.2019.2959275", "title": "Novel DTN Mobility-Driven Routing in Autonomous Drone Logistics Networks", "year": 2019, "publication_date": "2019-12-13", "type": "article", "language": "en", "authors": [ "Saeid Iranmanesh", "Raad Raad", "Muhammad Salman Raheel", "Faisel Tubbal", "Tony Jan" ], "first_author": "Saeid Iranmanesh", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Drones have become prevalent for the delivery of goods by many retail companies such as Amazon and Dominos. Amazon has an issued patent that describes how drones scan and collect data on their fly-overs while dropping off packages. In this context, we propose a path optimization algorithm for a drone multi-hop communications network that can carry and forward data in addition to its primary function of parcel deliveries. We argue that traditional Delay Tolerant Networking (DTN) based protocols may not be efficient for this purpose. Therefore, this paper proposes a new DTN-based algorithm that optimizes drone flight paths in conjunction with optimized routing to deliver both parcels and data in a power efficient way and within the shortest possible time. We propose a heuristic algorithm called Weighted Flight Path Planning (WFPP) that priorities the data packets in an exchange pool in order to create an optimized path for the drones. Our approach is to determine a weight for each packet based on the packet's remaining time to live, priority, size, and location of the packet's destination. When two drones meet each other, they exchange the high weighted packets. Simulation studies show that WFPP delivers up to 25% more packets compared with EBR, EPIDEMIC, and a similar path planning method. Also, WFPP reduces the data delivery delays by up to 66% while the overhead ratio is low.", "keywords": [ "Drone", "Computer science", "Network packet", "Overhead (engineering)", "Routing (electronic design automation)", "Computer network", "Shortest path problem", "Context (archaeology)", "Heuristic", "Path (computing)", "Real-time computing", "Graph" ], "cited_by_count": 53, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/8948470/08932497.pdf" }, { "id": "https://openalex.org/W4413468664", "doi": "10.2139/ssrn.5393526", "title": "Dynamic Order Fulfillment in Last-Mile Drone Delivery Under Demand Uncertainty", "year": 2025, "publication_date": "2025-01-01", "type": "preprint", "language": "en", "authors": [ "Linxuan Shi", "Zhengtian Xu", "Miguel A. Lejeune", "Qi Luo" ], "first_author": "Linxuan Shi", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Order (exchange)", "Computer science", "Aeronautics", "Operations research", "Business", "Engineering", "Geography", "Finance" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.5393526" }, { "id": "https://openalex.org/W4308789993", "doi": "10.1109/smap56125.2022.9942122", "title": "Last-Mile Delivery Options: Exploring Customer Preferences and Challenges", "year": 2022, "publication_date": "2022-11-03", "type": "conference-paper", "language": "en", "authors": [ "Evangelia Filiopoulou", "Cleopatra Bardaki", "Dimitrios Boukouvalas", "Μάρα Νικολαϊδου", "Panos E. Kourouthanassis" ], "first_author": "Evangelia Filiopoulou", "venue": null, "publisher": null, "abstract": "As consumers turn more and more to on-line shopping, requirements such as on time delivery and delivery cost saving are of major importance. Retail and logistics companies struggle to find strategies that offer a successful and fast last-mile delivery service that satisfies consumers’ preferences and expectations. Last-mile delivery is an opportunity, as well as a challenge for e-commerce retailers and logistics companies because it needs to satisfy customers’ preferences, offering the best customer experience. This paper explores Greek consumers’ preferences of last-mile delivery alternatives. We investigate the potential of using drone delivery and the challenges the consumers face during tracking their order delivery. We conducted a survey with 174 participants exploring their online shopping behavior, which delivery options they prefer, what delivery challenges they face (e.g. home delivery without prior notice) and which factors influence their delivery decisions (e.g. delivery time-flexibility and time saving). Keywords: Last-mile delivery, Drones, pick-up point", "keywords": [ "Last mile (transportation)", "Notice", "Business", "Mile", "Drone", "Flexibility (engineering)", "Service delivery framework", "Delivery Performance", "Marketing", "Order (exchange)", "Point (geometry)", "Service (business)" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/smap56125.2022.9942122" }, { "id": "https://openalex.org/W4377224967", "doi": "10.1007/s10479-023-05381-8", "title": "RETRACTED ARTICLE: A new truck-drone routing problem for parcel delivery by considering energy consumption and altitude", "year": 2023, "publication_date": "2023-05-22", "type": "article", "language": "en", "authors": [ "Maryam Momeni", "Seyed Mohammad Javad Mirzapour Al-e-Hashem", "Ali Akbar Heidari" ], "first_author": "Maryam Momeni", "venue": "Annals of Operations Research", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Computer science", "Heuristic", "Routing (electronic design automation)", "Energy consumption", "Solver", "Operations research", "Truck", "Theory of computation", "Mathematical optimization", "Metropolitan area", "Simulation" ], "cited_by_count": 18, "is_retracted": true, "is_paratext": false, "open_access_url": "https://link.springer.com/content/pdf/10.1007/s10479-023-05381-8.pdf" }, { "id": "https://openalex.org/W4408834109", "doi": "10.1016/j.tre.2025.104047", "title": "Parcel delivery by vehicle and drone in ordered customer neighborhoods", "year": 2025, "publication_date": "2025-03-25", "type": "article", "language": "en", "authors": [ "Ahmed Eisa Ghoniem", "Semih Boz", "Amro M. El-Adle" ], "first_author": "Ahmed Eisa Ghoniem", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Transport engineering", "Business", "Computer science", "Engineering" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2025.104047" }, { "id": "https://openalex.org/W4387682344", "doi": "10.1109/jiot.2023.3323704", "title": "Multidrone Parcel Delivery via Public Vehicles: A Joint Optimization Approach", "year": 2023, "publication_date": "2023-10-16", "type": "article", "language": "en", "authors": [ "Tianping Deng", "Xiaohui Xu", "Zhiqing Zou", "Wei Liu", "Desheng Wang", "Menglan Hu" ], "first_author": "Tianping Deng", "venue": "IEEE Internet of Things Journal", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "As one of the promising self-powered sensors on Internet of Things (IoT) platforms, unmanned aerial vehicles (UAVs) have attracted much attention for parcel delivery. Their high flexibility and low cost facilitate last-one-mile delivery. However, the limitations of battery capacity and payloads prevent drones from delivering independently over large scales. In this case, it is available to employ vehicles to assist the drones. The vehicles can be private-own trucks and vehicles in public transportation systems (PTSs). Compared to trucks, PTSs, such as buses and trains, do not require extra operating and fuel costs. Given these advantages, this article adopts PTSs to assist UAVs in parcel delivery. Nevertheless, the fixed routes and schedules of public vehicles pose new challenges to the routing and scheduling problem for PTS-assisted multidrone parcel delivery (RSPMD). To tackle the problem, we propose a novel routing and scheduling algorithm, referred to as the PTS-assisted multidrone parcel delivery (PDD) algorithm. Considering the schedules of the public vehicles, the algorithm jointly optimizes the distance and time cost of drones by iteratively combining parts of existing routes. To the best of our knowledge, we are the first to address RSPMD in which UAVs ride public vehicles to deliver parcels in a wide area. Simulation results are finally presented to demonstrate that PDD outperforms existing solutions in terms of effectiveness and efficiency.", "keywords": [ "Computer science", "Joint (building)", "Computer network", "Engineering" ], "cited_by_count": 36, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/jiot.2023.3323704" }, { "id": "https://openalex.org/W4285391602", "doi": "10.3390/app12147059", "title": "A Small UAV Optimized for Efficient Long-Range and VTOL Missions: An Experimental Tandem-Wing Quadplane Drone", "year": 2022, "publication_date": "2022-07-13", "type": "article", "language": "en", "authors": [ "Michał Okulski", "Maciej Ławryńczuk" ], "first_author": "Michał Okulski", "venue": "Applied Sciences", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Most types of Unmanned Aerial Vehicle (UAV, drone) missions requiring Vertical-Take-Off-and-Landing (VTOL) capability could benefit if a drone’s effective range could be extended. Example missions include Search-And-Rescue (SAR) operations, a remote inspection of distant objects, or parcel delivery. There are numerous research works on multi-rotor drones (e.g., quadcopters), fixed-wing drones, VTOL quadplanes, or tilt-motor/tilt-wing VTOLs. We propose a unique compact VTOL UAV optimized for long hover and long-range missions with great lifting capacity and manoeuvrability: a tandem-wing quadplane with fixed motors only. To the best of our knowledge, such a drone has not yet been researched. The drone was designed, built, and tested in flight. Construction details, its advantages, and issues are discussed in this research.", "keywords": [ "Drone", "Fixed wing", "Aeronautics", "Aerospace engineering", "Wing", "Computer science", "Range (aeronautics)", "Simulation", "Engineering" ], "cited_by_count": 26, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2076-3417/12/14/7059/pdf?version=1657704624" }, { "id": "https://openalex.org/W3003604482", "doi": "10.1109/indin41052.2019.8972170", "title": "When Drones Take Public Transport: Towards Low Cost and Large Range Parcel Delivery", "year": 2019, "publication_date": "2019-07-01", "type": "conference-paper", "language": "en", "authors": [ "Hailong Huang", "Andrey V. Savkin", "Chao Huang" ], "first_author": "Hailong Huang", "venue": null, "publisher": null, "abstract": "Though drones have become a promising tool for parcel delivery, due to the limited capacity of the on-board battery, their flight range is constrained. To enlarge the coverage range, the paper proposes a novel method, in which a parcel delivery drone can \"take\" a public transportation vehicle and travel on its roof. We investigate how to make use of the public transportation network to route the drone between the depot and a customer. Considering the complexity of the public transportation network, its randomness and time-dependency, instead of off-line planning a global optimal path, an adaptive algorithm is developed. Simulation results are presented to demonstrate how the proposed approach works.", "keywords": [ "Drone", "Public transport", "Computer science", "Randomness", "Range (aeronautics)", "Dependency (UML)", "Transport engineering", "Path (computing)", "Operations research", "Simulation", "Engineering", "Computer network" ], "cited_by_count": 16, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/indin41052.2019.8972170" }, { "id": "https://openalex.org/W4365460406", "doi": "10.1016/j.seta.2023.103202", "title": "Wind dynamic and energy-efficiency path planning for unmanned aerial vehicles in the lower-level airspace and urban air mobility context", "year": 2023, "publication_date": "2023-04-07", "type": "article", "language": "en", "authors": [ "Y.Y. Chan", "Kam K.H. Ng", "C.K.M. Lee", "Li‐Ta Hsu", "K. L. Keung" ], "first_author": "Y.Y. Chan", "venue": "Sustainable Energy Technologies and Assessments", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Voronoi diagram", "Context (archaeology)", "Energy consumption", "Computer science", "Dijkstra's algorithm", "Particle swarm optimization", "Shortest path problem", "Path (computing)", "Mathematical optimization", "Real-time computing", "Engineering", "Algorithm" ], "cited_by_count": 46, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.seta.2023.103202" }, { "id": "https://openalex.org/W4391678834", "doi": "10.1016/j.tcs.2024.114442", "title": "Approximation algorithms for drone delivery scheduling with a fixed number of drones", "year": 2024, "publication_date": "2024-02-09", "type": "article", "language": "en", "authors": [ "Saswata Jana", "Partha Sarathi Mandal" ], "first_author": "Saswata Jana", "venue": "Theoretical Computer Science", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Scheduling (production processes)", "Approximation algorithm", "Computer science", "Mathematical optimization", "Job shop scheduling", "Polynomial-time approximation scheme", "Algorithm", "Mathematics", "Computer network" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tcs.2024.114442" }, { "id": "https://openalex.org/W2982494512", "doi": "10.1109/ictis.2019.8883749", "title": "A Low-cost Simultaneous Localization And Mapping Algorithm For Last-mile Indoor Delivery", "year": 2019, "publication_date": "2019-07-01", "type": "conference-paper", "language": "en", "authors": [ "Wenmin Wang", "Wei Zhao", "Xiaohan Wang", "Zhihong Jin", "Yuanchen Li", "Troy Michael Runge" ], "first_author": "Wenmin Wang", "venue": null, "publisher": null, "abstract": "With the development of e-commerce, more and more express packages need to be delivered. The Last-mile indoor task always takes most time of a whole delivery due to the complex and unfamiliar indoor environment. Generally, there aren't enough existing indoor localization algorithms that are able to meet the business needs. To benefit the public, in this paper, an advanced low-cost and accurate intelligent localization and mapping algorithm is proposed. Three strengths, according to the experiment results, are concluded. First, the algorithm could run on Android devices, and it is able to save the cost of infrastructure as well as battery resources. Second, the algorithm can achieve an accuracy of less than 5cm, which is enough for general commercial purposes. Last, the system could intelligently shift the sensors between the Inertial Measurement Unit (IMU) sensors and the camera. To test our algorithm, we used the robot to execute the delivery of an indoor mailbox, obtaining a result of high accuracy (>95%) and low battery cost (saving more than 56%). Our algorithm is possible to be deployed in autonomous delivery vehicles or drones to provide last-mile delivery service.", "keywords": [ "Computer science", "Android (operating system)", "Drone", "Mile", "Real-time computing", "Inertial measurement unit", "Robot", "Embedded system", "Algorithm", "Artificial intelligence", "Operating system" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/ictis.2019.8883749" }, { "id": "https://openalex.org/W4389648585", "doi": "10.31075/pis.69.04.05", "title": "Last-mile delivery with electric vehicles, unmanned aerial vehicles, and e-scooters and e-bikes", "year": 2023, "publication_date": "2023-12-12", "type": "article", "language": "en", "authors": [ "Vladimir Ilin", "Marko Veličković", "Nemanja Garunović", "Dragan Simić" ], "first_author": "Vladimir Ilin", "venue": "Put i saobraćaj", "publisher": null, "abstract": "Intense growth of e-commerce over the last years has been recognized to have a strong impact on logistics and transportation, and particularly on different modes of last-mile deliveries in urban areas. Simultaneously, many European regulations have imposed strict environmental limitations in terms of decreased air and noise pollution in urban areas. In such circumstances, logistics and transportation sector needs to offer more efficient and more environmental ways to deliver goods. In this paper, we consider electric vehicles (EV) and different concepts of EVs, like unmanned aerial vehicles, e-scooters, and e-bikes as appropriate solutions for last-mile deliveries from the environmental perspective and lifecycle costs.", "keywords": [ "Mile", "Last mile (transportation)", "Transport engineering", "Noise pollution", "Electric vehicle", "Business", "Aeronautics", "Engineering", "Computer science", "Geography" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://putisaobracaj.rs/index.php/PiS/article/download/314/228" }, { "id": "https://openalex.org/W4200336297", "doi": "10.1080/03155986.2021.2012403", "title": "Identifying an effective last-mile customer delivery option with an integrated eco-friendly inventory model", "year": 2021, "publication_date": "2021-12-22", "type": "article", "language": "en", "authors": [ "Ivan Darma Wangsa", "Hui‐Ming Wee", "Yu-Lin Hsiao", "Novrianty Rizky" ], "first_author": "Ivan Darma Wangsa", "venue": "INFOR Information Systems and Operational Research", "publisher": "Taylor & Francis", "abstract": "In this study, we have developed an integrated inventory model for the last-mile delivery where the distributer supplies goods to his customers. Two services based on the type of deliveries are investigated, namely: 1) motorcycle delivery service, and 2) drone delivery service. The objective of this study is to identify an effective last-mile delivery option, considering both cost and eco-friendly factors. An algorithm is formulated to determine the optimal order quantity, safety factor, lead-time, total emission and the number of deliveries. The implication derived from our investigation is that: using motorcycle for the last-mile delivery may be faster than using drone, it is not as environmentally friendly. One of the disadvantages of using drone is the fact that current drone cannot carry too heavy loads or travel very long distances; we hope in the future more advanced drone will be able to overcome the disadvantage. Numerical examples and sensitivity analyses are provided to illustrate the proposed model. Finally, closing remarks and future research are given in the conclusion. From the comparison analysis, besides eco-friendly, the integrated total cost using drone is lower than motorcycle, with a cost-saving around 3-4%.", "keywords": [ "Drone", "Last mile (transportation)", "Environmentally friendly", "Mile", "Disadvantage", "Service (business)", "Lead time", "Computer science", "Closing (real estate)", "Transport engineering", "Operations management", "Operations research" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/03155986.2021.2012403" }, { "id": "https://openalex.org/W4414826128", "doi": "10.1016/j.tre.2025.104427", "title": "Optimizing autonomous multimodal last-mile delivery systems with time windows: Analyzing trade-offs between drones, robots, and trucks", "year": 2025, "publication_date": "2025-10-05", "type": "article", "language": "en", "authors": [ "Giovanni Campuzano", "Eduardo Lalla‐Ruiz", "Martijn Mes" ], "first_author": "Giovanni Campuzano", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": "This paper studies multi-modal last-mile delivery systems. More specifically, it introduces the Drone-Assisted Vehicle Routing Problem with Robot Stations and Time Windows (VRPD-RS-TW) to face exigent delivery schedules in last-mile logistics. The VRPD-RS-TW applies to highly populated city centers, where due to infrastructural issues, customers might be hard to reach by conventional trucks. This problem is characterized by utilizing three transportation modes: trucks, drones, and robots collaborating to deliver parcels and meet time window requirements. To solve this problem, we develop a Mixed Integer Linear Programming (MILP) formulation, valid inequalities to strengthen the linear relaxation, and a Three-Phased Granular Multi-Start Iterated Local Search (3P-GMS-ILS) metaheuristic algorithm. A computational study on instances of Amsterdam (the Netherlands) demonstrates that the 3P-GMS-ILS outperforms the MILP formulation and state-of-the-art metaheuristic approaches in terms of both objective function values and computational times. Furthermore, we provide insights into the effectiveness of the VRPD-RS-TW, showing that, under various cost scenarios, the combination of trucks, drones, and robots outperforms scenarios with fewer transportation modes. Across the studied cost scenarios, the VRPD-RS-TW simultaneously coordinates a higher volume of delivery operations, with 48.75 % performed by drones and robots, resulting in better objective function values than the related transportation systems. In scenarios where truck routing costs are lower than those of drones and robots, the VRPD-RS-TW still achieves better objective function values compared to the related transportation systems, although the share of drone and robot deliveries drops to 14.78 %. This shows that adding drones is not necessarily beneficial when trucks carry drones, as trucks should wait for drones, which might result in higher costs related to drone routing and drivers’ wages.", "keywords": [ "Iterated local search", "Metaheuristic", "Vehicle routing problem", "Benchmark (surveying)", "Truck", "Integer programming", "Linear programming", "Routing (electronic design automation)" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2025.104427" }, { "id": "https://openalex.org/W2234629990", "doi": null, "title": "Heuristic methods for the Traveling Salesman Problem with Drone.", "year": 2015, "publication_date": "2015-09-29", "type": "preprint", "language": "en", "authors": [ "Quang Minh Ha", "Yves Deville", "Quang-Dung Pham", "Minh Hoàng Hà" ], "first_author": "Quang Minh Ha", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "Over the past few years, unmanned aerial vehicles (UAV), also known as drones, have been adopted as part of a new logistic method in the commercial sector called last-mile delivery. In this novel approach, they are deployed alongside trucks to deliver goods to customers to improve the quality of service and reduce the transportation cost. This approach gives rise to a new variant of the traveling salesman problem (TSP), called TSP with drone (TSP-D). A variant of this problem that aims to minimize the time at which truck and drone finish the service (or, in other words, to maximize the quality of service) was studied in the work of Murray and Chu (2015). In contrast, this paper considers a new variant of TSP-D in which the objective is to minimize operational costs including total transportation cost and one created by waste time a vehicle has to wait for the other. The problem is first formulated mathematically. Then, two algorithms are proposed for the solution. The first algorithm (TSP-LS) was adapted from the approach proposed by Murray and Chu (2015), in which an optimal TSP solution is converted to a feasible TSP-D solution by local searches. The second algorithm, a Greedy Randomized Adaptive Search Procedure (GRASP), is based on a new split procedure that optimally splits any TSP tour into a TSP-D solution. After a TSP-D solution has been generated, it is then improved through local search operators. Numerical results obtained on various instances of both objective functions with different sizes and characteristics are presented. The results show that GRASP outperforms TSP-LS in terms of solution quality under an acceptable running time.", "keywords": [ "Travelling salesman problem", "Drone", "Traveling purchaser problem", "Truck", "Mathematical optimization", "Computer science", "2-opt", "Heuristic", "Greedy algorithm", "Service (business)", "Greedy randomized adaptive search procedure", "Local search (optimization)" ], "cited_by_count": 26, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1509.08764" }, { "id": "https://openalex.org/W7128585665", "doi": "10.1016/j.jairtraman.2026.102984", "title": "Optimising last-mile delivery network through locker–drone logistics system design under uncertain demand", "year": 2026, "publication_date": "2026-02-11", "type": "article", "language": "en", "authors": [ "Yunxiang Shu", "Kam K.H. Ng", "Wei Liu", "Zhongyi Jin", "Chenliang Zhang" ], "first_author": "Yunxiang Shu", "venue": "Journal of Air Transport Management", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Systems design", "Network planning and design", "Delivery system", "Flow network", "Humanitarian Logistics", "On demand", "Demand forecasting" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.jairtraman.2026.102984" }, { "id": "https://openalex.org/W4392305796", "doi": "10.5220/0012464100003639", "title": "Economic Sustainability in Last-Mile Drone Delivery Problem with Fulfillment Centers: A Mathematical Formulation", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Maria Elena Bruni", "Sara Khodaparasti", "Guido Perboli" ], "first_author": "Maria Elena Bruni", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Sustainability", "Computer science", "Operations research", "Engineering", "Geography" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.5220/0012464100003639" }, { "id": "https://openalex.org/W2921683784", "doi": "10.48550/arxiv.1903.04643", "title": "The Multi-objective Dynamic Traveling Salesman Problem: Last Mile Delivery with Unmanned Aerial Vehicles Assistance", "year": 2019, "publication_date": "2019-03-11", "type": "preprint", "language": "en", "authors": [ "Ben Remer", "Andreas A. Malikopoulos" ], "first_author": "Ben Remer", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "In this paper, we present an approach to optimizing the last-mile delivery route of a truck using coordination with unmanned aerial vehicles (UAVs). First, a traveling salesman problem is formulated to determine the truck's route. Then, a scheduling problem is formulated to determined the routes for the UAVs. A genetic algorithm is used to solve these problems, and simulated results are presented.", "keywords": [ "Travelling salesman problem", "Truck", "Mile", "Computer science", "Scheduling (production processes)", "Genetic algorithm", "Vehicle routing problem", "Job shop scheduling", "Mathematical optimization", "Real-time computing", "Engineering", "Automotive engineering" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1903.04643" }, { "id": "https://openalex.org/W4391338726", "doi": "10.1007/s13369-023-08681-0", "title": "Drone Applications in Logistics and Supply Chain Management: A Systematic Review Using Latent Dirichlet Allocation", "year": 2024, "publication_date": "2024-01-30", "type": "review", "language": "en", "authors": [ "Imen Zrelli", "Abderahman Rejeb", "Rawan Abusulaiman", "Raghad AlSahafi", "Karim Rejeb", "Mohammad Iranmanesh" ], "first_author": "Imen Zrelli", "venue": "Arabian Journal for Science and Engineering", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Latent Dirichlet allocation", "Drone", "Supply chain management", "Supply chain", "Computer science", "Mathematical optimization", "Mathematics", "Topic model", "Business", "Artificial intelligence", "Marketing" ], "cited_by_count": 40, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s13369-023-08681-0" }, { "id": "https://openalex.org/W4313293218", "doi": "10.3390/drones6120418", "title": "Study of Urban Logistics Drone Path Planning Model Incorporating Service Benefit and Risk Cost", "year": 2022, "publication_date": "2022-12-15", "type": "article", "language": "en", "authors": [ "Quan Shao", "Jiaming Li", "Ruoheng Li", "Jiangao Zhang", "Xiaobo Gao" ], "first_author": "Quan Shao", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The application of drones provides a powerful solution for “the last-mile” logistics services, while the large-scale implementation of logistics drone services will threaten the safety of buildings, pedestrians, vehicles, and other elements in the urban environment. The balance of risk cost and service benefit is accordingly crucial to managing logistics drones. In this study, we proposed a cost-benefit assessment model for quantifying risk cost and service benefit in the urban environment. In addition, a global heuristic path search rule was developed to solve the path planning problem based on risk mitigation and customer service. The cost-benefit assessment model quantifies the risk cost from three environmental elements (buildings, pedestrians, and vehicles) threatened by drone operations based on the collision probability, and the service benefit based on the characteristics of logistics service customers. To explore the effectiveness of the model in this paper, we simulate and analyse the effects of different risk combinations, unknown risk zones, and risk-benefit preferences on the path planning results. The results show that compared with the traditional shortest-distance method, the drone path planning method proposed in this paper can accurately capture the distribution of risks and customers in the urban environment. It is highly reusable in ensuring service benefits while reducing risk costs and generating a cost-effective path for logistics drones. We also compare the algorithm in this paper with the A* algorithm and verify that our algorithm improves the solution quality in complex environments.", "keywords": [ "Drone", "Service (business)", "Computer science", "Heuristic", "Path (computing)", "Motion planning", "Risk analysis (engineering)", "Operations research", "Transport engineering", "Business", "Engineering", "Marketing" ], "cited_by_count": 15, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/6/12/418/pdf?version=1671605429" }, { "id": "https://openalex.org/W4312429085", "doi": "10.1109/tem.2022.3210121", "title": "Evaluating Barriers to the Adoption of Delivery Drones in Rural Healthcare Supply Chains: Preparing the Healthcare System for the Future", "year": 2022, "publication_date": "2022-10-10", "type": "article", "language": "en", "authors": [ "Nitin Koshta", "Yashoda Devi", "Chetna Chauhan" ], "first_author": "Nitin Koshta", "venue": "IEEE Transactions on Engineering Management", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Emerging technologies, such as delivery drones have enormous potential to revolutionize the rural healthcare supply chain (RHSC) and assist the countries in achieving sustainable development goal 3: good health and well-being. The advantages of delivery drones include faster delivery, high responsiveness, and a lack of dependence on road infrastructure. Given these advantages, prior literature on drone delivery has extensively explored their applicability in last-mile delivery from the e-commerce or retailer's perspective. However, their applicability in RHSC from an academic as well as practical perspective is still at a nascent stage. The present study fills this gap by examining the barriers inhibiting the adoption of delivery drones in RHSC using the Grey Decision-Making Trial and Evaluation Laboratory technique. The results suggest that “lack of government regulations” is the most critical barrier. The study findings indicate that seven barriers are causal, and six are the effect barriers. “Limited load carrying capacity,” “low flight range,” and “difficulty in flying in adverse weather conditions” are the most prominent cause barriers. Moreover, “lack of skilled manpower,” “limited accuracy of navigation system,” and “lack of leadership commitment” are the most prominent effect barriers. We also perform sensitivity analysis to prove the robustness of the study output. The study results provide an in-depth understanding to the decision-makers and policymakers to help pave the way for the successful adoption of delivery drones in RHSC.", "keywords": [ "Health care", "Business", "Supply chain", "Public healthcare", "Healthcare delivery", "Drone", "Healthcare system", "Knowledge management", "Industrial organization", "Marketing", "Computer science", "Economic growth" ], "cited_by_count": 50, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tem.2022.3210121" }, { "id": "https://openalex.org/W3210501447", "doi": null, "title": "Last mile drone delivery services: Adoption barriers before and during the COVID-19 pandemic", "year": 2021, "publication_date": "2021-10-25", "type": "article", "language": "en", "authors": [ "Mario Schaarschmidt", "Matthias Bertram", "Marius Knobloch" ], "first_author": "Mario Schaarschmidt", "venue": "Journal of the Association for Information Systems", "publisher": "Association for Information Systems", "abstract": "The logistics market is facing considerable changes driven by digitalization and the continuously growing e-commerce sector. This has prompted logistics companies to search for innovative solutions that complement the dominant forms of last-mile parcel delivery. Specifically, new drone-based delivery technologies have reached a late development stage and offer advantages over the current truck delivery such as lower emissions and faster services. However, research on drone delivery adoption by end consumers is still in its infancies. In response to this research void, we conducted two surveys on consumers’ drone delivery service adoption intention and related risk perceptions – one before and one during the COVID-19 pandemic. With the two studies, we find robust support for the influence of drone-related risks on technology adoption. We further unravel differences that can be attributed to COVID-19, which generally has risen the need for contactless services. We discuss implications for IS theory and management.", "keywords": [ "Drone", "Coronavirus disease 2019 (COVID-19)", "Pandemic", "Mile", "Last mile (transportation)", "2019-20 coronavirus outbreak", "Aeronautics", "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)", "Computer science", "Business", "Engineering", "Geography" ], "cited_by_count": 2, "is_retracted": false, "is_paratext": false, "open_access_url": "https://aisel.aisnet.org/icis2021/is_implement/is_implement/3" }, { "id": "https://openalex.org/W3210049197", "doi": "10.1007/s00113-021-01095-3", "title": "Medical drones: Disruptive technology makes the future happen", "year": 2021, "publication_date": "2021-10-29", "type": "article", "language": "en", "authors": [ "Cyrus Sigari", "Peter Biberthaler" ], "first_author": "Cyrus Sigari", "venue": "Der Unfallchirurg", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Medical evacuation", "Disruptive technology", "Medical emergency", "Medicine", "Aeronautics", "Drone", "Engineering" ], "cited_by_count": 33, "is_retracted": false, "is_paratext": false, "open_access_url": "https://link.springer.com/content/pdf/10.1007/s00113-021-01095-3.pdf" }, { "id": "https://openalex.org/W7106272696", "doi": "10.1016/j.tre.2025.104538", "title": "The freight multimodal transport problem with buses and drones: An integrated approach for last-mile delivery", "year": 2025, "publication_date": "2025-11-21", "type": "article", "language": "en", "authors": [ "Jinfeng Yang", "Jiliu Li", "Hu Qin", "E Su", "Rui Zhang" ], "first_author": "Jinfeng Yang", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Integer programming", "Convergence (economics)", "Column generation", "Benders' decomposition", "Linear programming", "Decomposition", "Service (business)", "Key (lock)" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2025.104538" }, { "id": "https://openalex.org/W4396719852", "doi": "10.1016/j.tre.2024.103538", "title": "A risk-averse distributionally robust optimisation approach for drone-supported relief facility location problem", "year": 2024, "publication_date": "2024-05-08", "type": "article", "language": "en", "authors": [ "Zhongyi Jin", "Kam K.H. Ng", "Chenliang Zhang", "Wei Liu", "Fangni Zhang", "Gangyan Xu" ], "first_author": "Zhongyi Jin", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Facility location problem", "Robust optimization", "Computer science", "Operations research", "Mathematical optimization", "Engineering", "Mathematics" ], "cited_by_count": 51, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2024.103538" }, { "id": "https://openalex.org/W4392565526", "doi": "10.54033/icmr-003", "title": "STRATEGIC ANALYSIS FOR A TRUCK-DRONE HYBRID MODEL IN LAST MILE DELIVERY", "year": 2024, "publication_date": "2024-01-09", "type": "article", "language": "en", "authors": [ "José Francisco Tezei", "Claudia Regina De Freitas", "Antonio Lombardi Neto", "Paulo Cesar Chagas Rodrigues", "José Roberto Dale Luche" ], "first_author": "José Francisco Tezei", "venue": "International Contemporary Management Review", "publisher": null, "abstract": "The delivery sector, already on an upward trend prior to the Covid-19 pandemic, experienced a significant boost in demand for its services during the pandemic. However, the most expensive aspect for companies in this domain is the 'last mile' delivery costs, which can account for up to 45% of total logistics expenses. In light of this, our paper presents a study aiming to leverage this market trend to reduce company costs. We propose a hybrid model combining trucks and drones for last-mile delivery and conduct a market analysis for a company interested in developing this model. Drone deliveries are anticipated to grow at an annual rate of approximately 45%, outpacing the overall sector. This market outlook presents a compelling opportunity for entrepreneurs: the market is nascent, with a noticeable upward trend in both demand and investment. The truck-drone hybrid model, being up to 70% faster and 60% less expensive compared to traditional methods, offers dual benefits: enhanced customer satisfaction with lower expenditure, and reduced operational costs for companies while improving service quality. Despite pending regulatory challenges, the prevailing trend in technology advancements and major retailers' interest suggests a favorable outlook for legal approvals. As a novel technology, it naturally encounters some skepticism. Furthermore, drone usage has positive environmental implications, whether through alternative energy sources or traffic reduction, aligning well with the current ESG-driven market trends.", "keywords": [ "Drone", "Truck", "Mile", "Last mile (transportation)", "Aeronautics", "Computer science", "Transport engineering", "Business", "Engineering", "Automotive engineering", "Geography" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "https://icmreview.com/icmr/article/download/65/39" }, { "id": "https://openalex.org/W7154570543", "doi": "10.3390/su18083978", "title": "Strategic Planning for Sustainable Last-Mile Logistics: Balancing Airspace Constraints and Carbon Price Uncertainty in Truck-Drone Delivery", "year": 2026, "publication_date": "2026-04-16", "type": "article", "language": "en", "authors": [ "Chengyou Cui", "J J Li" ], "first_author": "Chengyou Cui", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The accelerated growth of e-commerce has intensified the dual challenges of weak infrastructure and carbon emission pressures in last-mile delivery for rural and mountainous regions. As the World Bank calls for integrating carbon market development into national strategies, Truck-Drone Collaborative Delivery (TDCD) has emerged as a critical sustainable solution. However, existing research often overlooks the strict airspace regulations in sensitive border areas. Therefore, this paper proposes a Vehicle Routing Problem with Drones and Mobile Base Stations (VRPDBS) model that explicitly incorporates airspace constraints and mobile hub deployment. We introduce a quantified “Regional Flyability Factor” (fk) to measure the impact of airspace restrictions on routing decisions and solve the problem using a hybrid metaheuristic algorithm. A case study based on real-world data from the Yanbian Korean Autonomous Prefecture reveals that strict airspace compliance imposes an absolute delivery delay of 4–5 h and an operational cost premium of up to 15%, an impact that can be effectively mitigated through a mobile base station mediation strategy. More importantly, multi-scenario sensitivity analysis under carbon price uncertainty indicates that although truck-dominant modes are cost-effective at current low carbon prices, drone-intensive configurations demonstrate superior economic robustness and environmental performance under high carbon price scenarios. This study not only provides a technical framework for green logistics planning in complex airspace but also offers strategic decision support for logistics enterprises to navigate long-term climate policy risks.", "keywords": [ "Robustness (evolution)", "Greenhouse gas", "Robust optimization", "Carbon price", "Decision support system", "Matching (statistics)", "Strategic planning" ], "cited_by_count": 3, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/18/8/3978/pdf?version=1776347601" }, { "id": "https://openalex.org/W4392975005", "doi": "10.1016/j.procs.2024.01.028", "title": "Acceptance Level of Drone Delivery among Malaysian Consumers", "year": 2024, "publication_date": "2024-01-01", "type": "conference-paper", "language": "en", "authors": [ "Soh Yee Fang", "Umi Kartini Rashid", "Lee Te Chuan" ], "first_author": "Soh Yee Fang", "venue": "Procedia Computer Science", "publisher": "Elsevier BV", "abstract": "Unmanned aerial vehicle (UAV) is the formal term for a drone that can operate without the pilot, or at ground level, the pilot can use the control operating systems. Today, some companies in Malaysia have begun to test drone parcel delivery, but the acceptance level of Malaysian consumers for this new service is still vague. Thus, the objectives of this study are to (i) measure the level of Malaysian consumer acceptance of drone delivery and (ii) investigate the relationships between perceived attribution of innovation, perceived risks, and individual characteristics and Malaysian consumer acceptance of drone delivery. A total of 158 Malaysian consumers who have knowledge of drones participated in this study through the convenience sampling technique. The data was collected using quantitative methods via an online questionnaire survey based on the Technology Acceptance Model (TAM), and Diffusion of Innovation (DOI). The results showed a high level of Malaysian consumer acceptance of drone delivery, with a mean value ranging from 3.91 to 4.11. Furthermore, the results demonstrated that compatibility (0.702), personal innovativeness (0.688), relative advantages of speed (0.659), complexity (0.627), relative advantages of environmental friendliness (0.612), mass media channel (0.527), and environmental concern (0.346) have positive significant affect toward drone delivery acceptance. However, delivery risks (0.038), privacy risks (0.043) and performance risks (0.019) were found to be insignificant towards the drone delivery acceptance. Ultimately, the study has management implications for companies readying to provide drone deliveries which can use this information to determine consumers' acceptance levels and improve drone delivery systems.", "keywords": [ "Computer science", "Drone", "Computer security" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.procs.2024.01.028" }, { "id": "https://openalex.org/W3092963479", "doi": "10.3390/electronics9101680", "title": "Methodology for Indoor Positioning and Landing of an Unmanned Aerial Vehicle in a Smart Manufacturing Plant for Light Part Delivery", "year": 2020, "publication_date": "2020-10-14", "type": "article", "language": "en", "authors": [ "Pedro Orgeira-Crespo", "Carlos Ulloa", "Guillermo Rey", "José Antonio Pérez García" ], "first_author": "Pedro Orgeira-Crespo", "venue": "Electronics", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Unmanned aerial vehicles (UAV) are spreading their usage in many areas, including last-mile distribution. In this research, a UAV is used for performing light parts delivery to workstation operators within a manufacturing plant, where GPS is no valid solution for indoor positioning. A generic localization solution is designed to provide navigation using RFID received signal strength measures and sonar values. A system on chip computer is onboarded with two missions: first, compute positioning and provide communication with backend software; second, provide an artificial vision system that cooperates with UAV’s navigation to perform landing procedures. An Industrial Internet of Things solution is defined for workstations to allow wireless mesh communication between the logistics vehicle and the backend software. Design is corroborated through experiments that validate planned solutions.", "keywords": [ "Global Positioning System", "Workstation", "Software", "Real-time computing", "Wireless", "Computer science", "Embedded system", "Positioning system", "Simulation", "Engineering", "Telecommunications", "Operating system" ], "cited_by_count": 28, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3390/electronics9101680" }, { "id": "https://openalex.org/W4410507396", "doi": "10.1108/rausp-07-2024-0146", "title": "Strategic insights into last-mile delivery: modelling the industry 4.0 enabler for e-commerce industry", "year": 2025, "publication_date": "2025-05-19", "type": "article", "language": "en", "authors": [ "Vijay Prakash Sharma", "Surya Prakash", "Ranbir Singh", "Ravindra Ojha", "Bharti Ramtiyal" ], "first_author": "Vijay Prakash Sharma", "venue": "RAUSP Management Journal", "publisher": null, "abstract": "Purpose Excellent customer experience with doorstep delivery is one of the motivations for online purchasing and e-commerce. Optimal technology-driven last-mile delivery is the backbone of this business model. This paper aims to identify industry 4.0 (I4.0) technology-based enablers for efficient e-commerce logistics for last-mile delivery (LMD) operations. Design/methodology/approach This study adopts an empirically grounded quantitative approach for defining and analysing the I4.0 technology enablers for efficient LMD operations. It adopts interpretive structural modelling and matrice d’impacts croisés multiplication appliquée á un classement analysis to identify the dependency and relationship among the identified enablers. Findings The transformation technologies of I4.0 offer a comprehensive package to handle LMD and e-commerce business challenges. This research identified that LMD and logistics will be dominated by autonomous running vehicles, drones and robots; apart from that, in I4.0 adoption cases, the implementation of radio-frequency identification was found suitable for efficient logistics networks. In addition, digitalisation through digital twins, robots, autonomous vehicles and Internet of Things adoption was found to drive the system and is crucial for strategic action. Research limitations/implications The findings of this research help companies and the e-commerce industry to evaluate strategic technological investments in promising I4.0 for LMD. The study also helps managers to focus on initiating and integrating digital technologies and autonomous vehicles, drones and robots focused on LMD improvement. Practical implications The findings of this research help companies and the e-commerce industry to evaluate strategic technological investments in promising I4.0 for LMD. The study also helps managers to focus on initiating and integrating digital technologies and autonomous vehicles, drones and robots focused on LMD improvement. Social implications Industry 4.0 technologies enable more efficient route planning, reducing fuel consumption and lowering carbon emissions. Optimised delivery networks reduce waste and ensure more efficient use of resources by using suggested technologies. Originality/value This study presents strategic insights into LMD and I4.0 enablers for the e-commerce environment. It proposes a theoretical framework that can serve as a roadmap for implementing I4.0 technologies to address unaddressed bottlenecks in LMD operations, lowering the logistics network’s efficiency.", "keywords": [ "Enabling", "Last mile (transportation)", "Mile", "Business", "E-commerce", "Marketing", "Industrial organization", "Commerce", "Computer science", "Geography", "World Wide Web", "Psychology" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.emerald.com/insight/content/doi/10.1108/RAUSP-07-2024-0146/full/pdf?title=strategic-insights-into-last-mile-delivery-modelling-the-industry-40-enabler-for-e-commerce-industry" }, { "id": "https://openalex.org/W4408493920", "doi": "10.1007/s13132-025-02680-2", "title": "A Way of Optimization of Last-Mile Logistics Operations. A Knowledge-Driven Literature review", "year": 2025, "publication_date": "2025-03-16", "type": "article", "language": "en", "authors": [ "Muhammad Ali Aslam", "Zhaolei Li" ], "first_author": "Muhammad Ali Aslam", "venue": "Journal of the Knowledge Economy", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Mile", "Entrepreneurship", "Last mile (transportation)", "Business", "Marketing", "Operations management", "Knowledge management", "Computer science", "Engineering", "Geography" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s13132-025-02680-2" }, { "id": "https://openalex.org/W7127401599", "doi": "10.1016/j.techfore.2026.124576", "title": "Sustainable last-mile delivery: Understanding perceived benefits and risks of AI-automated delivery drones in France", "year": 2026, "publication_date": "2026-02-03", "type": "article", "language": "en", "authors": [ "Lars Meyer‐Waarden", "Julien Cloarec", "Stéphane Salgado", "Vincent Favarin" ], "first_author": "Lars Meyer‐Waarden", "venue": "Technological Forecasting and Social Change", "publisher": "Elsevier BV", "abstract": "This study investigates the adoption of delivery drones in last-mile logistics by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with constructs related to well-being, perceived technology risk, privacy concerns, and environmental concerns. Drawing on a 2x2x2 experimental design involving 3212 French participants, we examine how physical accidents, cyberattacks, product criticality, and environmental values shape consumers' performance expectancy, social influence, risk perception, and behavioral intentions. The findings show that environmental concerns enhance the positive impact of performance expectancy and social influence on well-being, while unexpectedly reducing the negative effect of privacy concerns. Product criticality significantly weakens the relationship between well-being and adoption intention. This paper contributes theoretically by integrating sustainability and perceived risk theory into UTAUT2, thereby advancing understanding of how consumers evaluate novel autonomous technologies under conditions of uncertainty and ecological awareness. • Environmental concerns moderate the impact of perceived risks on well-being. • Higher product criticality weakens the positive influence of well-being on adoption. • Cyberattacks and accidents heighten perceived risks, lowering drone adoption.", "keywords": [ "Drone", "Expectancy theory", "Product (mathematics)", "Sustainability", "Risk perception", "Criticality", "Social influence", "New product development" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.techfore.2026.124576" }, { "id": "https://openalex.org/W4391953950", "doi": "10.3390/drones8030071", "title": "Genetic-Algorithm-Aided Deep Reinforcement Learning for Multi-Agent Drone Delivery", "year": 2024, "publication_date": "2024-02-20", "type": "article", "language": "en", "authors": [ "Farabi Ahmed Tarhan", "Nazım Kemal Üre" ], "first_author": "Farabi Ahmed Tarhan", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The popularity of commercial unmanned aerial vehicles has drawn great attention from the e-commerce industry due to their suitability for last-mile delivery. However, the organization of multiple aerial vehicles efficiently for delivery within limitations and uncertainties is still a problem. The main challenge of planning is scalability, since the planning space grows exponentially to the number of agents, and it is not efficient to let human-level supervisors structure the problem for large-scale settings. Algorithms based on Deep Q-Networks had unprecedented success in solving decision-making problems. Extension of these algorithms to multi-agent problems is limited due to scalability issues. This work proposes an approach that improves the performance of Deep Q-Networks on multi-agent delivery by drone problems by utilizing state decompositions for lowering the problem complexity, Curriculum Learning for handling the exploration complexity, and Genetic Algorithms for searching efficient packet-drone matching across the combinatorial solution space. The performance of the proposed method is shown in a multi-agent delivery by drone problem that has 10 agents and ≈1077 state–action pairs. Comparative simulation results are provided to demonstrate the merit of the proposed method. The proposed Genetic-Algorithm-aided multi-agent DRL outperformed the rest in terms of scalability and convergent behavior.", "keywords": [ "Drone", "Reinforcement learning", "Artificial intelligence", "Computer science", "Genetic algorithm", "Machine learning", "Biology", "Genetics" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/8/3/71/pdf?version=1708444862" }, { "id": "https://openalex.org/W4295860526", "doi": "10.2139/ssrn.4189367", "title": "Hybrid Truck-Drone Delivery Under Aerial Traffic Congestion", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "Ruifeng She", "Yanfeng Ouyang" ], "first_author": "Ruifeng She", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Truck", "Traffic congestion", "Transport engineering", "Computer science", "Aeronautics", "Automotive engineering", "Engineering", "Biology" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4189367" }, { "id": "https://openalex.org/W3124113257", "doi": null, "title": "Game of Drones - Viability Study of Drone Deliveries in Swedish Rural Last Mile Transport", "year": 2020, "publication_date": "2020-06-22", "type": "other", "language": "en", "authors": [ "Lena Persson", "Ling Liu" ], "first_author": "Lena Persson", "venue": "Gothenburg University Publications Electronic Archive (Gothenburg University)", "publisher": "University of Gothenburg", "abstract": "Problem discussion and objective: Despite its well-established networks of service points, Swedish logistics carriers are still facing many last mile challenges in terms of satisfying customers and becoming more sustainable while also being profitable. These challenges are expected to escalate especially in Swedish rural areas which cannot be solved by conventional methods. A drone is an unmanned aerial vehicle (UAV) which is an innovative transport mean featured with high flexibility and efficiency. It is regarded as a potential transport method in rural areas with poor infrastructure. Therefore, this study aims at examining the viability of drone deliveries in B2C last mile logistics in Swedish rural areas.\\nMethodology: This study firstly carried out a systematic literature review in the existing academic articles focusing on drone deliveries. Then, five Swedish rural municipalities were selected for conducting detailed research on and provided the ground for simulations. The simulation conceptualized the delivery routes in a real-life setting between service points and churches in order to compare the delivery time between vans and drones.\\nResults and Conclusion: The results show that although drone delivery has many development opportunities, it is not ready to be implemented at the present stage but may become a feasible solution in the future. Firstly, the legal framework supporting the integration of drones into logistics networks is well under way. Secondly, most of the delivery routes in the simulation are found to be time-saving with drones. But it has become less competitive due to its current technical constraints, in scenarios such as increased service coverage, ground vehicles driving in high-speed, or harsh weather. Thirdly, drones are more environmentally friendly than conventional vehicles. Fourthly, Swedish customers expect the home delivery of better service quality which poses additional opportunities especially in rural areas. Which makes drones to be a potential cost-effective solution for carriers with increased service level. Lastly, public acceptance currently of drone logistics is limited especially in Swedish rural areas of ageing society, which could be solved by deploying correct public relationship strategies with the maturity of previously discussed aspects.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Aeronautics", "Geography", "Engineering", "Biology" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/2077/64903" }, { "id": "https://openalex.org/W3047778227", "doi": "10.48550/arxiv.2005.00781", "title": "A Survey on Cellular-connected UAVs: Design Challenges, Enabling 5G/B5G\\n Innovations, and Experimental Advancements", "year": 2020, "publication_date": "2020-05-02", "type": "preprint", "language": "en", "authors": [ "Debashisha Mishra", "Enrico Natalizio" ], "first_author": "Debashisha Mishra", "venue": "arXiv (Cornell University)", "publisher": "Cornell University", "abstract": "As an emerging field of aerial robotics, Unmanned Aerial Vehicles (UAVs) have\\ngained significant research interest within the wireless networking research\\ncommunity. As soon as national legislations allow UAVs to fly autonomously, we\\nwill see swarms of UAV populating the sky of our smart cities to accomplish\\ndifferent missions: parcel delivery, infrastructure monitoring, event filming,\\nsurveillance, tracking, etc. The UAV ecosystem can benefit from existing 5G/B5G\\ncellular networks, which can be exploited in different ways to enhance UAV\\ncommunications. Because of the inherent characteristics of UAV pertaining to\\nflexible mobility in 3D space, autonomous operation and intelligent placement,\\nthese smart devices cater to wide range of wireless applications and use cases.\\nThis work aims at presenting an in-depth exploration of integration synergies\\nbetween 5G/B5G cellular systems and UAV technology, where the UAV is integrated\\nas a new aerial User Equipment (UE) to existing cellular networks. In this\\nintegration, the UAVs perform the role of flying users within cellular\\ncoverage, thus they are termed as cellular-connected UAVs (a.k.a. UAV-UE,\\ndrone-UE, 5G-connected drone, or aerial user). The main focus of this work is\\nto present an extensive study of integration challenges along with key 5G/B5G\\ntechnological innovations and ongoing efforts in design prototyping and field\\ntrials corroborating cellular-connected UAVs. This study highlights recent\\nprogress updates with respect to 3GPP standardization and emphasizes\\nsocio-economic concerns that must be accounted before successful adoption of\\nthis promising technology. Various open problems paving the path to future\\nresearch opportunities are also discussed.\\n", "keywords": [ "Computer science", "Cellular network", "Software deployment", "Drone", "Open research", "Field (mathematics)", "Standardization", "Wireless", "Systems engineering", "Telecommunications", "Engineering" ], "cited_by_count": 157, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2005.00781" }, { "id": "https://openalex.org/W4396910104", "doi": "10.1109/taes.2024.3400767", "title": "UAV Shore-to-Ship Parcel Delivery: Gust-Aware Trajectory Planning", "year": 2024, "publication_date": "2024-05-14", "type": "article", "language": "en", "authors": [ "Enrique Aldao", "Fernando Veiga-López", "H. González-Jorge", "Andry Maykol Pinto" ], "first_author": "Enrique Aldao", "venue": "IEEE Transactions on Aerospace and Electronic Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "This article presents a real-time trajectory calculation system for shore-to-ship operations using Unmanned Aerial Vehicles (UAVs). This is a concept, aimed to improve the efficiency of the transportation system by using UAVs to carry out parcel deliveries to offshore ships. During these operations, the UAVs would need to fly relatively close to manned vessels, posing significant risks for the crew in the event of any incident. Besides, in these marine areas the UAVs are exposed to meteorological phenomena such as wind gusts, which may compromise the stability of the flight and lead to potential collisions. Furthermore, this is a phenomenon difficult to predict, which poses a risk that must be considered in the operations. For these reasons, this work proposes a gust-aware multi-objective optimization solution for calculating fast and safe trajectories, considering the risk of flying in areas prone to the formation of intense gusts. Moreover, the system establishes a risk buffer with respect to all vessels to ensure compliance with EASA (European Union Aviation Safety Agency) regulations. For this purpose, Automatic Identification System (AIS) data are used to determine the position and velocity of the different vessels, and trajectory calculations are periodically updated based on their motion. The system computes the minimum-cost trajectory between the ground base and a moving destination ship while keeping these risk buffer constraints. The problem was solved through anOptimal Controlformulation discretized on a dynamic graph with time-dependent costs and constraints. The solution was obtained using a Reaching Method that allowed efficient and real-time computations.", "keywords": [ "Shore", "Trajectory", "Marine engineering", "Computer science", "Motion planning", "Aerospace engineering", "Engineering", "Meteorology", "Aeronautics", "Simulation", "Geology", "Artificial intelligence" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/taes.2024.3400767" }, { "id": "https://openalex.org/W4401548012", "doi": "10.1016/j.tre.2024.103709", "title": "Stochastic and robust truck-and-drone routing problems with deadlines: A Benders decomposition approach", "year": 2024, "publication_date": "2024-08-13", "type": "article", "language": "en", "authors": [ "Menghua Deng", "Yuanbo Li", "Jianpeng Ding", "Yanlin Zhou", "Lianming Zhang" ], "first_author": "Menghua Deng", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Truck", "Drone", "Benders' decomposition", "Decomposition", "Vehicle routing problem", "Computer science", "Routing (electronic design automation)", "Mathematical optimization", "Operations research", "Transport engineering", "Engineering", "Aerospace engineering" ], "cited_by_count": 35, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2024.103709" }, { "id": "https://openalex.org/W4404103745", "doi": "10.1080/00207543.2024.2422818", "title": "Enhancing offshore parcel delivery efficiency through vessel-unmanned aerial vehicle collaborative routing", "year": 2024, "publication_date": "2024-11-06", "type": "article", "language": "en", "authors": [ "Yantong Li", "Xingqi Wang" ], "first_author": "Yantong Li", "venue": "International Journal of Production Research", "publisher": "Taylor & Francis", "abstract": "Offshore oil and gas production is vital for global energy supply, but it faces logistical challenges due to the high costs and inefficiencies of traditional supply methods. This paper introduces the vessel-unmanned aerial vehicle (UAV) routing problem with multiple visits in a single flight (VURP-M), a novel logistical model that addresses aimed at enhancing the replenishment of offshore platforms with small, essential items. The VURP-M allows the UAV to perform multiple visits during a single flight, optimising the delivery process. To tackle the VURP-M, we propose two mixed-integer second-order cone programs that capture the problem's complexities. Given its NP-hard nature, we employ an adaptive large neighbourhood search (ALNS) method, featuring a segmented initialisation process and problem-specific operators guided by a rule-based mechanism to improve solution efficiency. The ALNS formulates an initial solution by solving a travelling salesman problem to create a giant tour, which is then used to group sequential targets into multiple UAV flights. The subsequent optimal resolution of a SOCP determines the take-off and landing points for each flight. Subsequently, the ALNS refines the initial solution through destroy and repair operators, enhancing the search for superior sequences and allocation schemes. The effectiveness of our approach is demonstrated through a real-world case study and numerical experiments on random instances featuring up to 100 platforms. The results offer implications of the collaborative vessel-UAV model for the offshore logistics industry.", "keywords": [ "Submarine pipeline", "Marine engineering", "Routing (electronic design automation)", "Vehicle routing problem", "Computer science", "Environmental science", "Transport engineering", "Engineering", "Computer network" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/00207543.2024.2422818" }, { "id": "https://openalex.org/W3135825682", "doi": "10.1109/itsc55140.2022.9922133", "title": "Dynamic Resource Management for Providing QoS in Drone Delivery Systems", "year": 2022, "publication_date": "2022-10-08", "type": "conference-paper", "language": "en", "authors": [ "Behzad Khamidehi", "Majid Raeis", "Elvino Silveira Sousa" ], "first_author": "Behzad Khamidehi", "venue": "2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)", "publisher": null, "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 drone 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 drones. 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 drones in use.", "keywords": [ "Drone", "Computer science", "Quality of service", "Bernoulli's principle", "Markov decision process", "Queueing theory", "Markov process", "Dynamic Bayesian network", "Resource allocation", "Mathematical optimization", "Distributed computing", "Queue" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/itsc55140.2022.9922133" }, { "id": "https://openalex.org/W4207060451", "doi": "10.1145/3491003.3491028", "title": "Greedy Algorithms for Scheduling Package Delivery with Multiple Drones", "year": 2022, "publication_date": "2022-01-04", "type": "conference-paper", "language": "en", "authors": [ "Francesco Betti Sorbelli", "Federico Corò", "Sajal Kumar Das", "Lorenzo Palazzetti", "Cristina Maria Pinotti" ], "first_author": "Francesco Betti Sorbelli", "venue": null, "publisher": null, "abstract": "Unmanned Aerial Vehicles (or drones) can be used for a myriad of civil applications, such as search and rescue, precision agriculture, or last-mile package delivery. Interestingly, the cooperation between drones and ground vehicles (trucks) can even enhance the quality of service. In this paper, we investigate the symbiosis among a truck and multiple drones in a last-mile package delivery scenario, introducing the Multiple Drone-Delivery Scheduling Problem (MDSP). From the main depot, a truck takes care of transporting a team of drones that will be used to deliver packages to customers. Each delivery is associated with a drone’s energy cost, a reward that characterizes the priority of the delivery, and a time interval representing the launch and rendezvous times from and to the truck. The objective of MDSP is to find an optimal scheduling for the drones that maximizes the overall reward subject to the drone’s battery capacity while ensuring that the same drone performs deliveries whose time intervals do not intersect. After showing that MDSP is an NP-hard problem, we devise an optimal Integer Linear Programming (ILP) formulation for it. Consequently, we design a heuristic algorithm for the single drone case and two more heuristic algorithms for the multiple drone case. Finally, we thoroughly compare the performance of our presented algorithms on different synthetic datasets.", "keywords": [ "Drone", "Computer science", "Scheduling (production processes)", "Integer programming", "Real-time computing", "Mathematical optimization", "Algorithm", "Mathematics" ], "cited_by_count": 21, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1145/3491003.3491028" }, { "id": "https://openalex.org/W4297178272", "doi": "10.1016/j.asoc.2022.109657", "title": "Adaptive mutant particle swarm optimization based precise cargo airdrop of unmanned aerial vehicles", "year": 2022, "publication_date": "2022-09-24", "type": "article", "language": "en", "authors": [ "An Zhang", "Han Xu", "Wenhao Bi", "Shuangfei Xu" ], "first_author": "An Zhang", "venue": "Applied Soft Computing", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Particle swarm optimization", "Computer science", "Differential evolution", "Position (finance)", "Premature convergence", "Flexibility (engineering)", "Convergence (economics)", "Process (computing)", "Control theory (sociology)", "Algorithm", "Mathematics", "Artificial intelligence" ], "cited_by_count": 25, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.asoc.2022.109657" }, { "id": "https://openalex.org/W4414449054", "doi": "10.1080/00207543.2025.2557530", "title": "An innovative framework integrating MILP and a parallel optimal algorithm for UAV-Enabled last-Mile delivery", "year": 2025, "publication_date": "2025-09-23", "type": "article", "language": "en", "authors": [ "Arash Amirteimoori", "Reza Kia", "Moataz Mohamed", "Gerhard‐Wilhelm Weber" ], "first_author": "Arash Amirteimoori", "venue": "International Journal of Production Research", "publisher": "Taylor & Francis", "abstract": "Urban last-mile delivery faces scalability, cost, and environmental challenges due to truck-based systems’ congestion and emissions. This study proposes a Customer-Centric UAV Last-Mile Delivery (CULMD) framework, eliminating truck dependency by optimising UAV routing, charging infrastructure, and sequencing for sustainable urban logistics. We introduce the Parallel Optimal Algorithm with MILP (POAM), a novel approach that decomposes the problem into two sub-problems: parallelised exact combinatorial optimisation for tour and parcel allocation, and MILP-based routing. POAM leverages multi-core CPU parallelisation to solve tour allocation across multiple regions and delivery windows concurrently, ensuring global optimality while reducing runtime by 21.5% compared to the Two-Stage Model (TSM) and 16-fold compared to the Integrated Model (IM). It outperforms metaheuristics like the Artificial Lemming Algorithm (ALA) and Hybrid Genetic Algorithm with Type-Aware Chromosomes (HGATAC+) by 12% and 11% in objective value, respectively. Sensitivity analyses show a 20% increase in regions cuts runtime by 68%, and a 20% increase in UAV load capacity reduces it by 22%. The CULMD framework, powered by POAM, advances sustainable logistics by minimising costs and environmental impacts, offering scalable solutions for urban delivery systems.", "keywords": [ "Optimal design", "Production (economics)", "Minification", "Key (lock)", "Algorithm design", "Efficient algorithm" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/00207543.2025.2557530" }, { "id": "https://openalex.org/W4393141992", "doi": "10.1111/deci.12628", "title": "Using intermediate points in parcel delivery operations with truck‐based autonomous drones", "year": 2024, "publication_date": "2024-03-25", "type": "article", "language": "en", "authors": [ "Bo Lan", "Yoshinori Suzuki" ], "first_author": "Bo Lan", "venue": "Decision Sciences", "publisher": "Wiley", "abstract": "Abstract Autonomous drones are no longer science fiction but are becoming reality. Prior studies have investigated how an autonomous drone can be used in conjunction with a parcel delivery truck, but they all restricted the drones’ launch/recovery sites to customer nodes visited by a truck. In practice, parcel carriers are considering the use of intermediate points (IPs), the sites found along the arcs connecting customer nodes, as drones' launch/recovery points. This means that the academic literature currently lags the industry practice. This article extends the previous works on truck‐and‐drone last‐mile delivery by investigating the conditions under which the use of IPs is beneficial by using both theoretical and empirical approaches. Our results show that, although using IPs is an effective concept that can save the cost (time) of package deliveries by 2.189% on average, the cost saving realized by using IPs can vary notably across carriers depending on their network characteristics. Specifically, our results suggest that the benefit of using IPs becomes high when a network has the following characteristics: (1) low customer density (a small number of customers served per square mile), and (2) large number of time‐sensitive packages (subject to time window constraints). Based on these findings, we provide normative implications on if, when, where, and to what extent IPs can be beneficial for the truck‐and‐drone joint operations in last‐mile logistics.", "keywords": [ "Drone", "Truck", "Computer science", "Operations research", "Operations management", "Business", "Mathematics", "Automotive engineering", "Engineering" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/deci.12628" }, { "id": "https://openalex.org/W4226256297", "doi": "10.1016/j.procs.2022.01.339", "title": "A novel mathematical approach for the Truck-and-Drone Location-Routing Problem", "year": 2022, "publication_date": "2022-01-01", "type": "conference-paper", "language": "en", "authors": [ "Laura Castro Montaña", "Laura Malagón-Alvarado", "Paola Andrea Miranda", "Mateo Montealegre Arboleda", "Elyn Lizeth Solano Charris", "Carlos Alberto Vega-Mejía" ], "first_author": "Laura Castro Montaña", "venue": "Procedia Computer Science", "publisher": "Elsevier BV", "abstract": "During the last decade, e-commerce has increased last-mile deliveries, impacting the (CO2) emissions footprint. Considering this environmental impact, sustainable technologies have emerged for transport operations, e.g., drones and electric vehicles. This paper deals with the Location-Routing Problem for delivering orders to a set of customers. The problem aims to minimize the total CO2 emissions due to freight transportation in last-mile deliveries with Trucks-and-Drones. A mathematical model is proposed for solving the problem. We test the model in different scenarios varying the number of clients (between 10 and 25), the number of trucks and drones (between 4 and 12 and between 5 and 13, respectively), and the available depots (i.e., between 5 and 15 parking lots). Our results provide insights on how shifting to cleaner transportation technologies can aid in the reduction of the carbon footprint of distribution activities and present a preamble of the significant impact that UAVs have in parcel delivery routing problems.", "keywords": [ "Drone", "Truck", "Computer science", "Carbon footprint", "Routing (electronic design automation)", "Vehicle routing problem", "Last mile (transportation)", "Operations research", "Transport engineering", "Footprint", "Mile", "Greenhouse gas" ], "cited_by_count": 23, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S1877050922003489/pdf" }, { "id": "https://openalex.org/W3099624069", "doi": null, "title": "An evaluation of the potential to use drone deliveries as last-mile logistics : In Jämtland", "year": 2020, "publication_date": "2020-01-01", "type": "dissertation", "language": "en", "authors": [ "Wout Desloovere" ], "first_author": "Wout Desloovere", "venue": "Publications (Mid Sweden University)", "publisher": "Mid Sweden University", "abstract": "The purpose of this thesis is to investigate the potential of delivery drones to contribute to the logistic network (specifically the last-mile), while reducing the environmental impact, in the region of Jämtland, Sweden. This is done by making a current technological overview of delivery drones. Using this summary, it is possible to estimate the possibilities of the technology itself. Best practises are gathered and analysed since it is valuable to learn from the previous experiences. The environmental impact of drone delivery is analysed because the main reason to use drones in Jämtland, should be to reduce the overall environmental impact of the logistic sector. This is combined with the legislation and challenges drones face. Hereby it is possible to determine when drone delivery could reduce the environmental impact of last-mile logistics. Drones or Unmanned Aerial Vehicles (UAV’s) are claimed by many companies (Google, Amazon, UPS) in the logistic sector to be a great technology for last-mile delivery, which is faced with high costs. Delivery drones promise to be cost reducing, fast and eco-friendly. There is a vast amount of research going into planning and economics of delivery drones for the logistic sector. The research on the environmental impact is limited and outcomes are highly dependent on the limitations of the study. Therefore, it is hard to analyse in which situations delivery drones can contribute to the society by lowering the environmental impact of the logistic sector, while following current trends of faster deliveries. The main findings are: the ideal case is a single light package or payload that needs to be transported, without the possibility for other packages to be delivered on the same route. Once package deliveries can be grouped in an efficient route, there are better technologies on the market nowadays. These are further developed and have a lower impact on the environment. Even if drones can be used in a way that benefits the environment and is cost-efficient, they still face challenges. More testing and scientific research is needed to prove drone delivery can be done in a safe manner, that benefits the environment while being cost-effective.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Aeronautics", "Business", "Engineering", "Operations management", "Geography" ], "cited_by_count": 1, "is_retracted": false, "is_paratext": false, "open_access_url": "http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-39193" }, { "id": "https://openalex.org/W4404689406", "doi": "10.1109/icds62089.2024.10756461", "title": "Mixed Electric Vehicles and UAVs for Last-Mile Delivery Under Ecological Objective", "year": 2024, "publication_date": "2024-10-23", "type": "conference-paper", "language": "en", "authors": [ "Bouhia Hanaa", "Jamal Benhra" ], "first_author": "Bouhia Hanaa", "venue": null, "publisher": null, "abstract": "The article introduces the Electric Vehicle Routing Problem with Drones (EVRPD), an innovative approach to optimizing last-mile delivery by integrating Electric Vehicles (EVs) with drones. The main goal is to minimize energy consumption and CO2 emissions while ensuring efficient delivery operations. This solution utilizes a mixed fleet of EVs as mother ships and drones for the final parcel delivery. EVs and drones are both capable of delivering parcels, with drones deployed for smaller and more urgent deliveries. The system focuses on optimizing the payload distribution to maximize energy efficiency and drone autonomy. Drones are replenished on the rooftops of EVs using IoT technology. To solve the routing problem, this solution employs bio-inspired algorithms such as Ant Colony Optimization (ACO) for EVs and Particle Swarm Optimization (PSO) for drones. This approach maximizes energy efficiency and drone autonomy while ensuring efficient parcel distribution. By integrating these innovative techniques, EVRPD offers promising prospects for a more sustainable and efficient urban logistics system.", "keywords": [ "Mile", "Last mile (transportation)", "Computer science", "Environmental science", "Ecology", "Transport engineering", "Geography", "Engineering", "Biology" ], "cited_by_count": 4, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/icds62089.2024.10756461" }, { "id": "https://openalex.org/W4388760395", "doi": "10.3390/drones7110679", "title": "Multi-UAV Urban Logistics Task Allocation Method Based on MCTS", "year": 2023, "publication_date": "2023-11-17", "type": "article", "language": "en", "authors": [ "Zeyuan Ma", "Jing Chen" ], "first_author": "Zeyuan Ma", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Unmanned aerial vehicles (UAVs) open new methods for efficient and rapid transportation in urban logistics distribution, where task allocation is a significant issue. In urban logistics systems, the energy status of UAVs is a critical factor in ensuring mission fulfillment. While extensive literature addresses the energy consumption of UAVs during tasks, the feasibility of energy replenishment must be addressed, which introduces additional uncertainty to the task allocation. This paper realizes multi-tasking, considering the energy consumption and replenishment of UAVs, to ensure that the tasks can be accomplished while reducing energy consumption. This paper proposes uniform distribution K-means to realize balanced multi-task grouping. Based on the Monte Carlo tree search (MCTS), a task-allocation-oriented MCTS method is proposed, including improving the selection and simulation process of MCTS. The aim was to collaborate with multiple trees for node selection and record historical simulation information to guide subsequent simulations for better results. Finally, the optimality of the proposed method was validated by comparing it with other relevant MCTS methods through several randomized experiments.", "keywords": [ "Computer science", "Task (project management)", "Energy consumption", "Process (computing)", "Node (physics)", "Monte Carlo tree search", "Selection (genetic algorithm)", "Energy (signal processing)", "Tree (set theory)", "Distributed computing", "Real-time computing", "Monte Carlo method" ], "cited_by_count": 22, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/7/11/679/pdf?version=1700233064" }, { "id": "https://openalex.org/W4386498420", "doi": "10.3390/en16186467", "title": "Quantitative and Comparative Analysis of Energy Consumption in Urban Logistics Using Unmanned Aerial Vehicles and Selected Means of Transport", "year": 2023, "publication_date": "2023-09-07", "type": "article", "language": "en", "authors": [ "Anna Kwasiborska", "Anna Stelmach", "Izabela Jabłońska" ], "first_author": "Anna Kwasiborska", "venue": "Energies", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Cities are moving towards sustainable development, which consists of tasks and challenges to improve the quality of life, and minimize energy consumption. The concept of sustainable mobility includes the choice of means of transport other than the car for all journeys, especially short distances, and for the delivery of goods. Due to the growing populations of cities, lack of free space, and high costs of building infrastructure for traditional means of transport, cities are looking for modern solutions that allow for the cheap, fast, and green transportation of people and goods. Urban air mobility is the answer to these problems, and uses eVTOL (electric vertical take-off and landing) aircraft and unmanned aerial vehicle systems (UAVs). The article’s main purpose is to present an energy efficiency analysis using UAVs and electric scooters in the transport of takeaway food, which is a solution that fits into the zero-emission transport policy. The article presents the following research problem: which type of electric transport (scooters/UAVs) shows a lower demand for electric energy when delivering food from restaurants to individual customers? The analysis method was applied using the D’Andrea, Dorling, Figliozzi, Kirchstein, and Tseng energy models. The completed calculations were used to perform a comparative analysis of energy consumption for three adopted scenarios related to energy consumption by drones.", "keywords": [ "Energy consumption", "Drone", "Sustainable transport", "Transport engineering", "Consumption (sociology)", "Environmental economics", "City logistics", "Energy (signal processing)", "Sustainable development", "Electric vehicle", "Automotive engineering", "Computer science" ], "cited_by_count": 10, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1996-1073/16/18/6467/pdf?version=1694086997" }, { "id": "https://openalex.org/W4313462136", "doi": "10.1145/3571306.3571411", "title": "Approximation Algorithms for Drone Delivery Packing Problem", "year": 2023, "publication_date": "2023-01-03", "type": "conference-paper", "language": "en", "authors": [ "Saswata Jana", "Partha Sarathi Mandal" ], "first_author": "Saswata Jana", "venue": null, "publisher": null, "abstract": "Recent advancements in unmanned aerial vehicles, also known as drones, have motivated logistics to use drones for multiple operations. Collaboration between drones and trucks in a last-mile delivery system has numerous benefits and reduces a number of challenges. In this paper, we introduce drone-delivery packing problem (DDP), where we have a set of deliveries and respective customers with their prescribed locations, delivery time intervals, associated cost for deliveries, and a set of drones with identical battery budgets. The objective of the DDP is to find an assignment for all deliveries to the drones by using the minimum number of drones subject to the battery budget and compatibility of the assignment of each drone. We prove that DDP is NP-Hard and formulate the integer linear programming (ILP) formulation for it. We proposed two greedy approximation algorithms for DDP. The first algorithm uses at most 2OPT + (Δ + 1) drones. The second algorithm uses at most 2OPT + ω drones, where OPT is the optimum solution for DDP, ω is the maximum clique size, and Δ is the maximum degree of the interval graph G constructed from the delivery time intervals.", "keywords": [ "Drone", "Computer science", "Approximation algorithm", "Integer programming", "Linear programming", "Mathematical optimization", "Set packing", "Set cover problem", "Set (abstract data type)", "Packing problems", "Algorithm", "Mathematics" ], "cited_by_count": 5, "is_retracted": false, "is_paratext": false, "open_access_url": "http://dx.doi.org/10.1145/3571306.3571411" }, { "id": "https://openalex.org/W4402728524", "doi": "10.3390/su16188037", "title": "Sustainability and New Technologies: Last-Mile Delivery in the Context of Smart Cities", "year": 2024, "publication_date": "2024-09-13", "type": "article", "language": "en", "authors": [ "K Andreas" ], "first_author": "K Andreas", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The purpose of this study is to conduct a literature review on urban last-mile logistics in the context of smart cities to help with defining the industry in new ways which involve space-wise innovations and the use of new technologies such as robotics, drones, IoT etc., toward a sustainable future. This literature review follows the SALSA approach and the CASP checklist, as well as several inclusion criteria for article collection. The results highlight the positive role of the industry 4.0 technologies and the role of smart cities in alleviating the last-mile logistics problem, while pinpointing that new initiatives such as dark stores and micro-fulfilment centers can also be a positive determinant of a more sustainable urban life. This is an original literature review which combines many important elements that come together in the context of smart cities and try to give some new perspectives to their last-mile logistics from viewpoints that have never been used before in similar research works. In addition, it can be used as a yardstick for future researchers who might try to dig dipper into the context of last-mile logistics, especially in smart cities.", "keywords": [ "Context (archaeology)", "Last mile (transportation)", "Sustainability", "Mile", "Business", "Smart city", "Architectural engineering", "Engineering", "Computer science", "Internet of Things", "Geography", "Computer security" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/16/18/8037/pdf?version=1726719803" }, { "id": "https://openalex.org/W4306148692", "doi": "10.1016/j.trb.2022.09.005", "title": "Planning reliable service facility location against disruption risks and last-mile congestion in a continuous space", "year": 2022, "publication_date": "2022-10-13", "type": "article", "language": "en", "authors": [ "Zhaodong Wang", "Siyang Xie", "Yanfeng Ouyang" ], "first_author": "Zhaodong Wang", "venue": "Transportation Research Part B Methodological", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Mile", "Last mile (transportation)", "Service (business)", "Space (punctuation)", "Computer science", "Transport engineering", "Operations management", "Business", "Engineering", "Geography", "Operating system", "Marketing" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trb.2022.09.005" }, { "id": "https://openalex.org/W3211754054", "doi": "10.1109/icws53863.2021.00092", "title": "A Holistic Service Provision Strategy for Drone-as-a-Service in MEC-based UAV Delivery", "year": 2021, "publication_date": "2021-09-01", "type": "conference-paper", "language": "en", "authors": [ "Liju Chu", "Xuejun Li", "Xu Jia", "Azadeh Ghari Neiat", "Xiao Liu" ], "first_author": "Liju Chu", "venue": null, "publisher": null, "abstract": "With the rapid growth of Internet of Things (IoT), Mobile Edge Computing (MEC) is becoming the major platform for many smart systems such as smart logistics, smart healthcare, and smart transportation, given its lower latency and higher reliability compared with centralized cloud computing. There is a growing interest in Drone-as-a-Service in recent years which enables the MEC-based smart UAV delivery system. However, most existing works on Drone-as-a-Service focus on the static service composition or the dynamic service provisioning, rather than a holistic service provisioning strategy for the entire UAV delivery process. In this paper, we propose a holistic service provisioning strategy for Drone-as-a-Service in MEC-based UAV delivery to address such an issue. Specifically, a MEC-based UAV relay delivery system framework (RDS) is designed, which considers both the static stage for provisioning delivery services and the dynamic stage for provisioning computing services. Based on the service models for both static and dynamic stages, an energy-efficient service provision strategy (ESP-GA) for MEC-based UAV last-mile delivery is proposed, which aims to minimize the overall energy consumption under deadline constraints. Through the simulation experiments based on a prototype UAV delivery system, the experimental results have successfully demonstrated the superior performance of the proposed holistic strategy in comparison with several representative service provisioning strategies.", "keywords": [ "Provisioning", "Computer science", "Cloud computing", "Drone", "Service delivery framework", "Service (business)", "Computer network", "Edge computing", "Operating system" ], "cited_by_count": 17, "is_retracted": false, "is_paratext": false, "open_access_url": "https://figshare.com/articles/conference_contribution/A_Holistic_Service_Provision_Strategy_for_Drone-as-a-Service_in_MEC-based_UAV_Delivery/20651118" }, { "id": "https://openalex.org/W4389941392", "doi": "10.1016/j.cie.2023.109851", "title": "Learning for multiple purposes: A Q-learning enhanced hybrid metaheuristic for parallel drone scheduling traveling salesman problem", "year": 2023, "publication_date": "2023-12-18", "type": "article", "language": "en", "authors": [ "Ping Chen", "Qianlong Wang" ], "first_author": "Ping Chen", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Metaheuristic", "Computer science", "Scheduling (production processes)", "Mathematical optimization", "Job shop scheduling", "Reinforcement learning", "Heuristic", "Artificial intelligence", "Operations research", "Engineering" ], "cited_by_count": 47, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2023.109851" }, { "id": "https://openalex.org/W4379232034", "doi": "10.3389/fpubh.2023.1128886", "title": "Implementation of drone based delivery of medical supplies in North-East India: experiences, challenges and adopted strategies", "year": 2023, "publication_date": "2023-06-02", "type": "article", "language": "en", "authors": [ "Sumit Suresh Aggarwal", "Prakamya Gupta", "Nupur Mahajan", "Sivaraman Balaji", "Khangembam Jitenkumar Singh", "Balram Bhargava", "Samiran Panda" ], "first_author": "Sumit Suresh Aggarwal", "venue": "Frontiers in Public Health", "publisher": "Frontiers Media", "abstract": "Timely delivery of medical supplies is essential in the healthcare sector, which is hampered by factors such as poor transportation network, traffic and adverse environmental conditions. Alternatively, drone operations can leapfrog the last mile logistic solutions in hard-to-reach terrains. The present paper elucidates the implementation process of drone-based delivery of medical supplies, operational challenges and innovations adopted by scientists in Manipur and Nagaland. Three districts, Bishnupur, Imphal West and Churachandpur from Manipur and two districts, Mokokchung and Tuensang from Nagaland, were selected for the study. Regulatory and ethical approvals and coordination with state health and administrative authorities were accorded. Implementation and operational challenges faced by the research team were recorded elaborately in the field diaries and assessed qualitatively. The experiences encountered by the team for case-to-case based permission and coordination with the central and state aviation authorities, district administration and health authorities were observed. The drone-related technical and logistic challenges were identified as the deployment of suitable drones, payload capacity, time management for operations, and transportation of drones. The officials adopted mitigation strategies to overcome field-based challenges. Drone-based deliveries of medical supplies are proving to be time efficient, however, overcoming operational challenges could provide an effective long-term deployment strategy.", "keywords": [ "Drone", "Software deployment", "Business", "Payload (computing)", "Operations management", "Process management", "Computer science", "Computer security", "Engineering" ], "cited_by_count": 48, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.frontiersin.org/articles/10.3389/fpubh.2023.1128886/pdf" }, { "id": "https://openalex.org/W4384932819", "doi": "10.1080/19427867.2023.2237736", "title": "Optimal routing and scheduling of unmanned aerial vehicles for delivery services", "year": 2023, "publication_date": "2023-07-19", "type": "article", "language": "en", "authors": [ "Shangyao Yan", "Ching-Sheng Sun", "Yi-Hsuan Chen" ], "first_author": "Shangyao Yan", "venue": "Transportation Letters", "publisher": "Taylor & Francis", "abstract": "In the logistics industry, unmanned aerial vehicles (UAVs) are mostly used for last-mile delivery, in combination with other types of vehicles. There is currently no operator in Taiwan that is completely reliant upon the usage of UAVs for cargo delivery services. Therefore, this study proposes a routing and scheduling model for UAVs by utilizing the network flow technique and mathematical programming methods. All advance requests must be satisfied, and the related operating constraints ensured in the model. The model aims to minimize the total operating cost. To effectively solve large problems that may occur in practice, this study develops a relax-and-fix heuristic. Numerical tests are conducted to preliminarily examine whether the model, coupled with the heuristic algorithm, could be applied in practice. The test results indicate that the proposed model and solution algorithm are effective and thus could be useful for UAV operators to perform delivery routing and scheduling.", "keywords": [ "Computer science", "Scheduling (production processes)", "Vehicle routing problem", "Heuristic", "Routing (electronic design automation)", "Flow network", "Operations research", "Mathematical optimization", "Distributed computing", "Computer network", "Engineering", "Operations management" ], "cited_by_count": 15, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/19427867.2023.2237736" }, { "id": "https://openalex.org/W4377090877", "doi": "10.3390/systems11050259", "title": "A Hybrid Metaheuristic Solution Method to Traveling Salesman Problem with Drone", "year": 2023, "publication_date": "2023-05-19", "type": "article", "language": "en", "authors": [ "Noyan Sebla Günay", "Emre Çakmak", "Serol Bulkan" ], "first_author": "Noyan Sebla Günay", "venue": "Systems", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The challenging idea of using drones in last-mile delivery systems of logistics addresses a new routing problem referred to as the traveling salesman problem with drone (TSP-D). TSP-D aims to construct a route to deliver parcels to a set of customers by either a truck or a drone, thereby minimizing operational costs. Since TSP-D is considered NP-hard, using metaheuristics is one of the most promising solutions. This paper presents a hybrid metaheuristic solution method of TSP-D based on two state-of-the-art algorithms: the genetic algorithm and ant colony optimization algorithm. Heuristics in TSP-D literature are based on two consequent decisions: truck routing and drone assignment. Unlike those in the existing literature, the proposed metaheuristic constructs both truck and drone routes simultaneously. Additionally, to the best of our knowledge, we introduce for the first time a solution method on the basis of an ant colony optimization approach to TSP-D. Additionally, we propose a binary pheromone framework for both drone and truck, diverging from the traditional pheromone structure. Computational experiments indicate that the proposed hybrid metaheuristic algorithm is able to generate optimal routes for provided instances of TSP-D benchmarking. In addition, the algorithm improves the best-known solutions of some instances found by rival heuristics.", "keywords": [ "Metaheuristic", "Drone", "Travelling salesman problem", "Ant colony optimization algorithms", "Computer science", "Heuristics", "Mathematical optimization", "Vehicle routing problem", "Genetic algorithm", "Routing (electronic design automation)", "Ant colony", "Parallel metaheuristic" ], "cited_by_count": 31, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2079-8954/11/5/259/pdf?version=1684492686" }, { "id": "https://openalex.org/W4407176841", "doi": "10.30574/wjarr.2025.25.2.0214", "title": "Artificial Intelligence in Logistics and Distribution: The function of AI in dynamic route planning for transportation, including self-driving trucks and drone delivery systems", "year": 2025, "publication_date": "2025-02-05", "type": "article", "language": "en", "authors": [ "Yetunde Adeoye", "Erumusele Francis Onotole", "Tunde Ogunyankinnu", "Godwin Aipoh", "Akintunde Akinyele Osunkanmibi", "JOSEPH EGBEMHENGHE" ], "first_author": "Yetunde Adeoye", "venue": "World Journal of Advanced Research and Reviews", "publisher": "GSC Online Press", "abstract": "Artificial Intelligence (AI) is revolutionizing logistics and distribution by enhancing efficiency, reducing costs, and improving the overall delivery experience. One of the key applications of AI in this sector is dynamic route optimization, where machine learning algorithms analyze real-time data such as traffic patterns, weather conditions, and road closures to continuously adjust delivery routes. This reduces fuel consumption, optimizes delivery times, and mitigates operational disruptions. In parallel, autonomous delivery systems, including drones and self-driving trucks, are transforming last-mile and long-haul transportation by minimizing human intervention and increasing speed and reliability. AI-powered autonomous delivery systems leverage advanced technologies such as computer vision, sensors, and machine learning to navigate and make real-time decisions. Drones, for example, are already being utilized for time-sensitive deliveries, especially in remote or underserved areas, while self-driving trucks promise to revolutionize long-haul freight transportation with the potential for 24/7 operation, cost reduction, and increased safety. Despite the clear benefits, challenges such as regulatory frameworks, safety concerns, and public acceptance remain as significant barriers to large-scale adoption. This review explores the role of AI in dynamic route optimization, drones, and self-driving trucks within logistics, providing insights into how these technologies are currently being implemented and the challenges that lie ahead. It further discusses the potential for AI to reshape the future of logistics and transportation by driving innovation in automation, reducing operational inefficiencies, and contributing to the development of smarter, more sustainable supply chains. The future of AI in logistics promises a more integrated, cost-effective, and agile system that can adapt to global challenges and evolving consumer demands.", "keywords": [ "Truck", "Drone", "Function (biology)", "Transport engineering", "Self driving", "Computer science", "Route planning", "Engineering", "Aerospace engineering" ], "cited_by_count": 17, "is_retracted": false, "is_paratext": false, "open_access_url": "https://journalwjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-0214.pdf" }, { "id": "https://openalex.org/W4205292877", "doi": "10.1002/net.22087", "title": "The multivisit drone routing problem with edge launches: An iterative approach with discrete and continuous improvements", "year": 2022, "publication_date": "2022-01-04", "type": "article", "language": "en", "authors": [ "Adriano Masone", "Stefan Poikonen", "Bruce Golden" ], "first_author": "Adriano Masone", "venue": "Networks", "publisher": "Wiley", "abstract": "Abstract In recent years, the usage of drones in last‐mile logistics has stirred great interest in the operations research community. Many papers have considered schemes of hybrid truck‐and‐drone delivery. In this paper, we focus on the Multivisit Drone Routing Problem with Edge Launches (MVDRP‐EL) which assumes: a heterogenous set of packages, a drone capable of carrying multiple packages at a time and that can be launched and retrieved along an edge, a flexible launch/retrieval site set, and a user‐defined energy depletion function. We believe this paper is the first to exploit edge launch ability through a global continuous approach. In this context, we propose an original formulation based on the Covering Salesman Problem to compute a valid lower bound for the problem and an iterative solution method to determine a MVDRP‐EL solution with quality launch/retrieval sites along the road network edges. Each iteration of the solution method consists of two phases. In the first phase, the road network edges are discretized to obtain launch/retrieval sites, and a first solution is determined. In the second phase, the truck route is set and we reduce the completion time by carefully synchronizing truck and drone routes by solving an original Mixed Integer Second Order Cone Program. The lower bound formulation and the proposed method have been tested on several instances and results indicate the effectiveness of the proposed method and the potential value of launching along an edge, respectively.", "keywords": [ "Drone", "Synchronizing", "Computer science", "Context (archaeology)", "Truck", "Enhanced Data Rates for GSM Evolution", "Set (abstract data type)", "Routing (electronic design automation)", "Mathematical optimization", "Mathematics", "Computer network", "Engineering" ], "cited_by_count": 35, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/net.22087" }, { "id": "https://openalex.org/W4404957831", "doi": "10.3390/drones8120724", "title": "Synthetic Dataset Generation for Optimizing Multimodal Drone Delivery Systems", "year": 2024, "publication_date": "2024-11-30", "type": "article", "language": "en", "authors": [ "Diyar Altinses", "David Orlando Salazar Torres", "Asrat Mekonnen Gobachew", "Stefan Lier", "Andreas Schwung" ], "first_author": "Diyar Altinses", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Street delivery faces significant challenges due to outdated road infrastructure, which was not designed to handle current vehicle volumes, leading to congestion and inefficiencies, especially in last-mile delivery. Integrating drones into the delivery system offers a promising solution by bypassing congested roads, thereby enhancing delivery speed and reducing infrastructure strain. However, optimizing this multimodal delivery system is complex and data-driven, with real-world data often being costly and restricted. To address this, we propose a synthetic dataset generator that creates diverse and realistic delivery scenarios, incorporating environmental variables, customer profiles, and vehicle characteristics. The key contribution of our work is the development of a dynamic generator for multiple optimization problems with diverse complexities or even combinations of optimization problems. This generator allows for the incorporation of real-world factors such as traffic congestion and synthetically generated factors such as wind conditions and communication constraints, as well as others. The primary objective is to establish a foundation for creating benchmark scenarios that enable the comparison of existing and new approaches. We evaluate the generated dataset by applying it to three optimization problems, including facility location, vehicle routing, and path planning, using different techniques to demonstrate the dataset’s effectiveness and operational viability.", "keywords": [ "Computer science", "Drone", "Key (lock)", "Benchmark (surveying)", "Last mile (transportation)", "Generator (circuit theory)", "Delivery Performance", "Multimodal transport", "Routing (electronic design automation)", "Transport engineering", "Engineering", "Industrial engineering" ], "cited_by_count": 7, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3390/drones8120724" }, { "id": "https://openalex.org/W4323361884", "doi": "10.3390/vaccines11030605", "title": "The Use of Drones to Deliver Rift Valley Fever Vaccines in Rwanda: Perceptions and Recommendations", "year": 2023, "publication_date": "2023-03-07", "type": "article", "language": "en", "authors": [ "Evan F. Griffith", "Janna M. Schurer", "Billy Mawindo", "Rita Kwibuka", "Thierry Turibyarive", "Janetrix Hellen Amuguni" ], "first_author": "Evan F. Griffith", "venue": "Vaccines", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Given the recent emergence of Rift Valley Fever (RVF) in Rwanda and its profound impact on livelihoods and health, improving RVF prevention and control strategies is crucial. Vaccinating livestock is one of the most sustainable strategies to mitigate the impact of RVF on health and livelihoods. However, vaccine supply chain constraints severely limit the effectiveness of vaccination programs. In the human health sector, unmanned aerial vehicles, i.e., drones, are increasingly used to improve supply chains and last-mile vaccine delivery. We investigated perceptions of whether delivering RVF vaccines by drone in Rwanda might help to overcome logistical constraints in the vaccine supply chain. We conducted semi-structured interviews with stakeholders in the animal health sector and Zipline employees in Nyagatare District in the Eastern Province of Rwanda. We used content analysis to identify key themes. We found that stakeholders in the animal health sector and Zipline employees believe that drones could improve RVF vaccination in Nyagatare. The primary benefits study participants identified included decreased transportation time, improved cold chain maintenance, and cost savings.", "keywords": [ "Rift Valley fever", "Livelihood", "Business", "Drone", "Vaccination", "Supply chain", "Environmental health", "Geography", "Medicine", "Marketing", "Agriculture", "Virology" ], "cited_by_count": 29, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2076-393X/11/3/605/pdf?version=1678161395" }, { "id": "https://openalex.org/W2794669607", "doi": "10.2139/ssrn.3096573", "title": "Responsible Design of Drones and Drone Services - A Synthetic Report", "year": 2018, "publication_date": "2018-01-01", "type": "preprint", "language": "en", "authors": [ "Haomiao Du", "Michiel A. Heldeweg" ], "first_author": "Haomiao Du", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Drone", "Aeronautics", "Engineering", "Computer security", "Business", "Computer science", "Biology" ], "cited_by_count": 15, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.3096573" }, { "id": "https://openalex.org/W4399580298", "doi": "10.3390/su16124995", "title": "An Energy-Efficient Logistic Drone Routing Method Considering Dynamic Drone Speed and Payload", "year": 2024, "publication_date": "2024-06-12", "type": "article", "language": "en", "authors": [ "Kunpeng Wu", "Shaofeng Lu", "Haoqin Chen", "Minling Feng", "Zenghao Lu" ], "first_author": "Kunpeng Wu", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Unmanned aerial vehicles (UAVs), or drones, are recognized for their potential to improve efficiency in last-mile delivery. Unlike the vehicle routing problem, drone route design is challenging due to several operational signatures, such as speed optimization, multi-trip operation, and energy consumption estimation. Drone energy consumption is a nonlinear function of both speed and payload. Moreover, the high speed of drones can significantly curtail the drone range, thereby limiting the efficiency of drone delivery systems. This paper addresses the trade-off between speed and flight range in a multi-trip drone routing problem with variable flight speeds (DRP–VFS). We propose a new model to specifically consider energy constraints using a nonlinear energy consumption model and treat drone speeds as decision variables. The DRP–VFS is initially formulated using mixed-integer linear programming (MILP) to minimize energy consumption. To solve large-scale instances, we propose a three-phase adaptive large neighborhood search (ALNS) algorithm and compare its performance with a commercial MIP solver. The experimental results demonstrate that the proposed method is capable of effectively identifying suboptimal solutions in practical scenarios. Furthermore, results indicate that operating drones at variable speeds leads to about 21% energy savings compared to fixed speeds, with advantages in cost savings and range extension.", "keywords": [ "Drone", "Payload (computing)", "Energy consumption", "Computer science", "Routing (electronic design automation)", "Range (aeronautics)", "Mathematical optimization", "Real-time computing", "Engineering", "Aerospace engineering", "Embedded system", "Mathematics" ], "cited_by_count": 14, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3390/su16124995" } ]