[ { "id": "https://openalex.org/W2471190594", "doi": "10.1109/tsmc.2016.2582745", "title": "Vehicle Routing Problems for Drone Delivery", "year": 2016, "publication_date": "2016-07-14", "type": "article", "language": "en", "authors": [ "Kevin Dorling", "Jordan Heinrichs", "Geoffrey G. Messier", "Sebastian Magierowski" ], "first_author": "Kevin Dorling", "venue": "IEEE Transactions on Systems Man and Cybernetics Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Unmanned aerial vehicles, or drones, have the potential to significantly reduce the cost and time of making last-mile deliveries and responding to emergencies. Despite this potential, little work has gone into developing vehicle routing problems (VRPs) specifically for drone delivery scenarios. Existing VRPs are insufficient for planning drone deliveries: either multiple trips to the depot are not permitted, leading to solutions with excess drones, or the effect of battery and payload weight on energy consumption is not considered, leading to costly or infeasible routes. We propose two multitrip VRPs for drone delivery that address both issues. One minimizes costs subject to a delivery time limit, while the other minimizes the overall delivery time subject to a budget constraint. We mathematically derive and experimentally validate an energy consumption model for multirotor drones, demonstrating that energy consumption varies approximately linearly with payload and battery weight. We use this approximation to derive mixed integer linear programs for our VRPs. We propose a cost function that considers our energy consumption model and drone reuse, and apply it in a simulated annealing (SA) heuristic for finding suboptimal solutions to practical scenarios. To assist drone delivery practitioners with balancing cost and delivery time, the SA heuristic is used to show that the minimum cost has an inverse exponential relationship with the delivery time limit, and the minimum overall delivery time has an inverse exponential relationship with the budget. Numerical results confirm the importance of reusing drones and optimizing battery size in drone delivery VRPs.", "keywords": [ "Drone", "Payload (computing)", "Computer science", "Energy consumption", "Mathematical optimization", "Simulation", "Mathematics", "Engineering", "Computer network", "Network packet", "Electrical engineering" ], "cited_by_count": 1343, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1608.02305" }, { "id": "https://openalex.org/W1977319619", "doi": "10.1016/j.trc.2015.03.005", "title": "The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery", "year": 2015, "publication_date": "2015-03-25", "type": "article", "language": "en", "authors": [ "Chase C. Murray", "Amanda Chu" ], "first_author": "Chase C. Murray", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Heuristics", "Truck", "Last mile (transportation)", "Computer science", "Travelling salesman problem", "Vehicle routing problem", "Operations research", "Scheduling (production processes)", "Routing (electronic design automation)", "Engineering", "Operations management" ], "cited_by_count": 1726, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2015.03.005" }, { "id": "https://openalex.org/W4282970004", "doi": "10.3390/drones6060147", "title": "Towards the Unmanned Aerial Vehicles (UAVs): A Comprehensive Review", "year": 2022, "publication_date": "2022-06-15", "type": "article", "language": "en", "authors": [ "Syed Agha Hassnain Mohsan", "Muhammad Asghar Khan", "Fazal Noor", "Insaf Ullah", "Mohammed H. Alsharif" ], "first_author": "Syed Agha Hassnain Mohsan", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Recently, unmanned aerial vehicles (UAVs), also known as drones, have come in a great diversity of several applications such as military, construction, image and video mapping, medical, search and rescue, parcel delivery, hidden area exploration, oil rigs and power line monitoring, precision farming, wireless communication and aerial surveillance. The drone industry has been getting significant attention as a model of manufacturing, service and delivery convergence, introducing synergy with the coexistence of different emerging domains. UAVs offer implicit peculiarities such as increased airborne time and payload capabilities, swift mobility, and access to remote and disaster areas. Despite these potential features, including extensive variety of usage, high maneuverability, and cost-efficiency, drones are still limited in terms of battery endurance, flight autonomy and constrained flight time to perform persistent missions. Other critical concerns are battery endurance and the weight of drones, which must be kept low. Intuitively it is not suggested to load them with heavy batteries. This study highlights the importance of drones, goals and functionality problems. In this review, a comprehensive study on UAVs, swarms, types, classification, charging, and standardization is presented. In particular, UAV applications, challenges, and security issues are explored in the light of recent research studies and development. Finally, this review identifies the research gap and presents future research directions regarding UAVs.", "keywords": [ "Drone", "Payload (computing)", "Computer science", "Standardization", "Variety (cybernetics)", "Systems engineering", "Aeronautics", "Computer security", "Engineering", "Artificial intelligence" ], "cited_by_count": 917, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/6/6/147/pdf?version=1655300789" }, { "id": "https://openalex.org/W2789343279", "doi": "10.1016/j.ijdrr.2018.02.020", "title": "A drone fleet model for last-mile distribution in disaster relief operations", "year": 2018, "publication_date": "2018-02-16", "type": "article", "language": "en", "authors": [ "Boualem Rabta", "Christian Wankmüller", "Gerald Reiner" ], "first_author": "Boualem Rabta", "venue": "International Journal of Disaster Risk Reduction", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Last mile (transportation)", "Payload (computing)", "Truck", "Mile", "Operations research", "Humanitarian Logistics", "Humanitarian aid", "Transport engineering", "Emergency management", "Integer programming", "Distribution (mathematics)" ], "cited_by_count": 339, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2212420918302000/pdf" }, { "id": "https://openalex.org/W3087935424", "doi": "10.1007/s00291-020-00607-8", "title": "Last-mile delivery concepts: a survey from an operational research perspective", "year": 2020, "publication_date": "2020-09-21", "type": "article", "language": "en", "authors": [ "Nils Boysen", "Stefan Fedtke", "Stefan Schwerdfeger" ], "first_author": "Nils Boysen", "venue": "OR Spectrum", "publisher": "Springer Science+Business Media", "abstract": "Abstract In the wake of e-commerce and its successful diffusion in most commercial activities, last-mile distribution causes more and more trouble in urban areas all around the globe. Growing parcel volumes to be delivered toward customer homes increase the number of delivery vans entering the city centers and thus add to congestion, pollution, and negative health impact. Therefore, it is anything but surprising that in recent years many novel delivery concepts on the last mile have been innovated. Among the most prominent are unmanned aerial vehicles (drones) and autonomous delivery robots taking over parcel delivery. This paper surveys established and novel last-mile concepts and puts special emphasis on the decision problems to be solved when setting up and operating each concept. To do so, we systematically record the alternative delivery concepts in a compact notation scheme, discuss the most important decision problems, and survey existing research on operations research methods solving these problems. Furthermore, we elaborate promising future research avenues.", "keywords": [ "Last mile (transportation)", "Mile", "Computer science", "Drone", "Perspective (graphical)", "Operations research", "Planner", "Engineering", "Geography" ], "cited_by_count": 623, "is_retracted": false, "is_paratext": false, "open_access_url": "https://link.springer.com/content/pdf/10.1007/s00291-020-00607-8.pdf" }, { "id": "https://openalex.org/W2998391831", "doi": "10.1016/j.ijpe.2019.107598", "title": "Two echelon vehicle routing problem with drones in last mile delivery", "year": 2019, "publication_date": "2019-12-27", "type": "article", "language": "en", "authors": [ "Patchara Kitjacharoenchai", "Byung‐Cheol Min", "Seokcheon Lee" ], "first_author": "Patchara Kitjacharoenchai", "venue": "International Journal of Production Economics", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Computer science", "Heuristics", "Routing (electronic design automation)", "Vehicle routing problem", "Swap (finance)", "Scheduling (production processes)", "Integer programming", "Operations research", "Mathematical optimization", "Computer network" ], "cited_by_count": 332, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ijpe.2019.107598" }, { "id": "https://openalex.org/W4317743226", "doi": "10.3390/drones7020077", "title": "Last-Mile Drone Delivery: Past, Present, and Future", "year": 2023, "publication_date": "2023-01-21", "type": "article", "language": "en", "authors": [ "Hossein Eskandaripour", "Enkhsaikhan Boldsaikhan" ], "first_author": "Hossein Eskandaripour", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Sustainable green products and services garner more attention from companies and enterprises that aim to succeed and grow in highly competitive markets by imposing less harms on the environment and ecosystems. Last-mile delivery from local distribution centers to customers plays an essential role in the retail business. Retail companies are leaning towards implementing green, efficient transportation methods, such as drones, in their last-mile delivery operations to conserve ecosystems. Accordingly, researchers have documented numerous research findings on last-mile drone delivery in recent years. This literature review selected a collection of articles mostly from 2011 to 2022 and reviewed them in terms of key technical challenges, such as routing, cargo distribution optimization, battery management, data communication, and environmental protection. These challenges are interrelated in a sense of achieving eco-friendly, efficient, lean, last-mile drone delivery. The selection of these technical challenges is based on the top challenges discussed in the literature.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "Business", "Marketing", "Geography" ], "cited_by_count": 154, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/7/2/77/pdf?version=1675067807" }, { "id": "https://openalex.org/W2915338839", "doi": "10.1016/j.trc.2019.11.003", "title": "The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones", "year": 2019, "publication_date": "2019-12-13", "type": "article", "language": "en", "authors": [ "Chase C. Murray", "Ritwik Raj" ], "first_author": "Chase C. Murray", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Truck", "Heuristic", "Computer science", "Mathematical optimization", "Automation", "Integer (computer science)", "Integer programming", "Operations research", "Real-time computing", "Simulation" ], "cited_by_count": 566, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2019.11.003" }, { "id": "https://openalex.org/W2952541788", "doi": "10.1186/s12544-019-0368-2", "title": "Last mile delivery by drones: an estimation of viable market potential and access to citizens across European cities", "year": 2019, "publication_date": "2019-06-20", "type": "article", "language": "en", "authors": [ "Jean-Philippe Aurambout", "Konstantinos Gkoumas", "Biagio Ciuffo" ], "first_author": "Jean-Philippe Aurambout", "venue": "European Transport Research Review", "publisher": "Springer Science+Business Media", "abstract": "Rapid technological developments in autonomous unmanned aerial vehicles (UAV or drones) and an evolving legislation may soon open the way for their large-scale implementation in the last mile delivery of products. The use of drones could drastically decrease labour costs and has been hyped as a potential disruptor to the parcel delivery industry. Online retailers and delivery companies such as Amazon, are already filing up patents for the development of multi-level fulfilment centres for unmanned aerial vehicles or “drone-beehives” that would allow the deployment of this technology within built environment. A substantial amount of research has been carried out in the last years on the potential use of drones for parcel delivery, principally in the area of logistic optimisation. However, little is known about the potential market and economic viability of such services in Europe. This paper presents a modelling framework using EU-wide high-resolution population and land-use data to estimate the potential optimal location of drone-beehives based on economic viability criterion. It estimates the potential number of EU28 citizens that could potentially benefit from last mile-drone delivery services under four scenarios. The performed analyses indicates that under the scenario considered as the most technologically realistic, up to 7% of EU citizens could get access to such services. When considering technological improvements scenarios, the share reaches 30%. Furthermore, results suggest that due to the differences in population and land-use patterns in the different Member States, the potential drone coverage across Europe could be very heterogeneous, with the UK, Germany, Italy and France appearing as the most likely countries where drone-beehives may have the most efficient development.", "keywords": [ "Drone", "Population", "Last mile (transportation)", "Software deployment", "Business", "Legislation", "Mile", "Transport engineering", "Engineering", "Geography" ], "cited_by_count": 315, "is_retracted": false, "is_paratext": false, "open_access_url": "https://etrr.springeropen.com/track/pdf/10.1186/s12544-019-0368-2" }, { "id": "https://openalex.org/W2935841433", "doi": "10.1016/j.apenergy.2019.03.117", "title": "Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization", "year": 2019, "publication_date": "2019-03-22", "type": "article", "language": "en", "authors": [ "Wen‐Chyuan Chiang", "Yuyu Li", "Jennifer S. Shang", "Timothy L. Urban" ], "first_author": "Wen‐Chyuan Chiang", "venue": "Applied Energy", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Carbon footprint", "Greenhouse gas", "Sustainability", "Flexibility (engineering)", "Vehicle routing problem", "Energy consumption", "Exploit", "Routing (electronic design automation)", "Truck", "Computer science", "Integer programming" ], "cited_by_count": 394, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.apenergy.2019.03.117" }, { "id": "https://openalex.org/W3185842095", "doi": "10.1080/13675567.2021.1957803", "title": "Consumers’ perceptions of last mile drone delivery", "year": 2021, "publication_date": "2021-07-26", "type": "article", "language": "en", "authors": [ "Steven Leon", "Charlie Chen", "Aaron Ratcliffe" ], "first_author": "Steven Leon", "venue": "International Journal of Logistics Research and Applications", "publisher": "Taylor & Francis", "abstract": "Organisations have begun testing last mile drone delivery and will likely push to use it more in the near future. This research examines the influence of privacy, legislation, organisational trust, and usefulness on consumers’ intention to adopt last mile drone delivery services. Partial Least Squares – Structural Equation Modelling is used to evaluate the measurement and structural models. Sample data were collected from Amazon Mechanical Turk using an online survey. The analysis shows that as perceived privacy risk increases, the intention to adopt drone delivery service decreases. Additionally, privacy disposition influences privacy concerns and that both privacy concerns and legislative protections each influence perceived privacy risk. Further, perceived usefulness has the greatest influence on consumers’ intention to adopt drones for delivery. Even more, as consumers see drone delivery as more useful, their perceived privacy risk is reduced. Trust further influences consumers’ intention to adopt drones for delivery.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "Business", "Perception", "Marketing", "Computer science", "Advertising", "Geography", "Psychology" ], "cited_by_count": 104, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/13675567.2021.1957803" }, { "id": "https://openalex.org/W3155782751", "doi": "10.1016/j.tre.2021.102325", "title": "Potentialities of drones and ground autonomous delivery devices for last-mile logistics", "year": 2021, "publication_date": "2021-04-13", "type": "article", "language": "en", "authors": [ "Clément Lemardelé", "Miquel Estrada", "Laia Pagès", "Mónika Bachofner" ], "first_author": "Clément Lemardelé", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Last mile (transportation)", "Boom", "Truck", "Externality", "Context (archaeology)", "Computer science", "Transport engineering", "Operations research", "City logistics", "Mile", "Engineering" ], "cited_by_count": 226, "is_retracted": false, "is_paratext": false, "open_access_url": "http://www.sciencedirect.com/science/article/pii/S1366554521000995" }, { "id": "https://openalex.org/W2984182507", "doi": "10.1016/j.apm.2019.11.020", "title": "A truck and drones model for last-mile delivery: A mathematical model and heuristic approach", "year": 2019, "publication_date": "2019-11-18", "type": "article", "language": "en", "authors": [ "Mohammad Moshref‐Javadi", "Ahmad Hemmati", "Matthias Winkenbach" ], "first_author": "Mohammad Moshref‐Javadi", "venue": "Applied Mathematical Modelling", "publisher": "Elsevier BV", "abstract": "We present a mathematical formulation and a heuristic solution approach for the optimal planning of delivery routes in a multi-modal system combining truck and Unmanned Aerial Vehicle (UAV) operations. In this system, truck and UAV operations are synchronized, i.e., one or more UAVs travel on a truck, which serves as a mobile depot. Deliveries can be made by both UAVs and the truck. While the truck follows a multi-stop route, each UAV delivers a single shipment per dispatch. The presented optimization model minimizes the waiting time of customers in the system. The model determines the optimal allocation of customers to truck and UAVs, the optimal route sequence of the truck, and the optimal launch and reconvene locations of the UAVs along the truck route. We formulate the problem as a Mixed-Integer Linear Programming (MILP) model and conduct a bound analysis to gauge the maximum potential of the proposed system to reduce customer waiting time compared to a traditional truck-only delivery system. To be able to solve real-world problem size instances, we propose an efficient Truck and Drone Routing Algorithm (TDRA). The solution quality and computational performance of the mathematical model and the TDRA are compared together and with the truck-only model based on a variety of problem instances. Further, we apply the TDRA to a real-world case study for e-commerce delivery in São Paulo, Brazil. Our numerical results suggest significant reductions in customer waiting time to be gained from the proposed multi-modal delivery model.", "keywords": [ "Truck", "Heuristic", "Drone", "Computer science", "Integer programming", "Last mile (transportation)", "Routing (electronic design automation)", "Vehicle routing problem", "Operations research", "Real-time computing", "Transport engineering", "Engineering" ], "cited_by_count": 232, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S0307904X19306936/pdf" }, { "id": "https://openalex.org/W4386906053", "doi": "10.1016/j.trd.2023.103831", "title": "Drones in last-mile delivery: A systematic review on Efficiency, Accessibility, and Sustainability", "year": 2023, "publication_date": "2023-09-20", "type": "review", "language": "en", "authors": [ "Vipul Kumar Garg", "Suman Niranjan", "Victor R. Prybutok", "Terrance L. Pohlen", "David Marius Gligor" ], "first_author": "Vipul Kumar Garg", "venue": "Transportation Research Part D Transport and Environment", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Sustainability", "Last mile (transportation)", "Mile", "Government (linguistics)", "Business", "Engineering", "Geography" ], "cited_by_count": 216, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trd.2023.103831" }, { "id": "https://openalex.org/W3009632634", "doi": "10.1016/j.trc.2020.01.019", "title": "Joint optimization of customer location clustering and drone-based routing for last-mile deliveries", "year": 2020, "publication_date": "2020-03-06", "type": "article", "language": "en", "authors": [ "Mohamed Salama", "Sharan Srinivas" ], "first_author": "Mohamed Salama", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Truck", "Last mile (transportation)", "Cluster analysis", "Heuristic", "Operations research", "Key (lock)", "Real-time computing", "Mile", "Artificial intelligence", "Engineering" ], "cited_by_count": 241, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2020.01.019" }, { "id": "https://openalex.org/W2990601306", "doi": "10.1287/trsc.2017.0791", "title": "Optimization Approaches for the Traveling Salesman Problem with Drone", "year": 2018, "publication_date": "2018-04-06", "type": "article", "language": "en", "authors": [ "Niels A.H. Agatz", "Paul Bouman", "Marie Evans Schmidt" ], "first_author": "Niels A.H. Agatz", "venue": "Transportation Science", "publisher": "Institute for Operations Research and the Management Sciences", "abstract": "The fast and cost-efficient home delivery of goods ordered online is logistically challenging. Many companies are looking for new ways to cross the last mile to their customers. One technology-enabled opportunity that recently has received much attention is the use of drones to support deliveries. An innovative last-mile delivery concept in which a truck collaborates with a drone to make deliveries gives rise to a new variant of the traveling salesman problem (TSP) that we call the TSP with drone. In this paper, we model this problem as an integer program and develop several fast route-first, cluster-second heuristics based on local search and dynamic programming. We prove worst-case approximation ratios for the heuristics and test their performance by comparing the solutions to the optimal solutions for small instances. In addition, we apply our heuristics to several artificial instances with different characteristics and sizes. Our experiments show that substantial savings are possible with this concept compared to truck-only delivery. The online appendix is available at https://doi.org/10.1287/trsc.2017.0791 .", "keywords": [ "Travelling salesman problem", "Drone", "Heuristics", "Truck", "Computer science", "Mathematical optimization", "Vehicle routing problem", "Local search (optimization)", "Operations research", "Lin–Kernighan heuristic", "2-opt", "Routing (electronic design automation)" ], "cited_by_count": 1036, "is_retracted": false, "is_paratext": false, "open_access_url": "https://repub.eur.nl/pub/78472/ERS-2015-011-062016.pdf" }, { "id": "https://openalex.org/W2801247784", "doi": "10.1016/j.tele.2018.04.014", "title": "Drone delivery: Factors affecting the public’s attitude and intention to adopt", "year": 2018, "publication_date": "2018-05-01", "type": "article", "language": "en", "authors": [ "Wonsang Yoo", "Eun Jung Yu", "Jaemin Jung" ], "first_author": "Wonsang Yoo", "venue": "Telematics and Informatics", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Business", "Marketing", "Truck", "Affect (linguistics)", "Residence", "Service (business)", "Internet privacy", "Advertising", "Computer science", "Psychology", "Engineering" ], "cited_by_count": 338, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tele.2018.04.014" }, { "id": "https://openalex.org/W4210983798", "doi": "10.1108/ijpdlm-01-2021-0013", "title": "Consumer preferences for innovative and traditional last-mile parcel delivery", "year": 2022, "publication_date": "2022-02-11", "type": "article", "language": "en", "authors": [ "Rico Merkert", "Michiel C.J. Bliemer", "Muhammad Fayyaz" ], "first_author": "Rico Merkert", "venue": "International Journal of Physical Distribution & Logistics Management", "publisher": "Emerald Publishing Limited", "abstract": "Purpose The purpose of this research is to reveal consumer preferences towards innovative last-mile parcel delivery and more specifically unmanned aerial delivery drones, in comparison to traditional postal delivery (postie) and the recent rise of parcel lockers in Australia. The authors investigate competitive priorities and willingness to pay for key attributes of parcel delivery (mode, speed, method and time window), the role of contextual moderators such as parcel value and security and opportunities for logistics service providers in the growing e-commerce market. Design/methodology/approach A survey involving stated choice experiments has been conducted among 709 respondents in urban Australia. The authors estimated panel error component logit models, derived consumer priorities and deployed 576 Monte Carlo simulations to forecast potential delivery mode market shares. Findings The study results suggest that people prefer postie over drone delivery, all else equal, but that drone deliveries become competitive with large market shares if they live up to the premise that they can deliver faster and cheaper. Both drone and postie become less attractive relative to parcel lockers when there is no safe place to leave a parcel at a residence, highlighting the importance of situational context and infrastructure at the receiving end of last-mile delivery. The authors identified opportunities for chargeable add-on services, such as signature for postie and 2-h parcel deliveries for drones. Originality/value The authors offer timely and novel insights into consumers preferences towards aerial drone parcel deliveries compared to postie and lockers. Going beyond the extant engineering/operations research literature, the authors provide a starting point and add new dimensions/moderators for last-mile parcel delivery choice analysis and empirical evidence of market potential and competitive attributes of innovative versus traditional parcel delivery alternatives.", "keywords": [ "Last mile (transportation)", "Drone", "Context (archaeology)", "Marketing", "Business", "Value proposition", "Mile", "Geography" ], "cited_by_count": 131, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/2123/28556" }, { "id": "https://openalex.org/W4210290495", "doi": "10.1109/tits.2021.3138432", "title": "DroneTalk: An Internet-of-Things-Based Drone System for Last-Mile Drone Delivery", "year": 2022, "publication_date": "2022-02-03", "type": "article", "language": "en", "authors": [ "Kuan‐Wen Chen", "Ming-Ru Xie", "Yumin Chen", "Ting-Tsan Chu", "Yi‐Bing Lin" ], "first_author": "Kuan‐Wen Chen", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "At present, drone delivery systems usually function only in global positioning system (GPS)-friendly environments and thus cannot deliver goods into customers’ houses, which is an element of urban last-mile delivery. In this study, we investigated solutions for enabling drones to fly autonomously in mixed indoor–outdoor environments. We propose a novel Internet of Things (IoT)-based drone delivery system, namely DroneTalk, for mail delivery. DroneTalk combines a GPS, an inertial measurement unit, and visual information to achieve mixed indoor–outdoor autopilot operation. Furthermore, DroneTalk integrates an autonomous drone control system with an IoT device management platform to enable a drone to achieve automatic online weather awareness. Most importantly, DroneTalk is a novel work considering communication, processing, and control latencies simultaneously during autopilot operation to avoid problems related to drone collisions. These problems have always existed but become more serious when drones are flying close to buildings. Simulation results indicate that the proposed system can attain a high user-defined flight success rate (i.e., 99% in our simulations) without any collisions; thus, the proposed system can be feasibly used in real-world environments.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "The Internet", "Aeronautics", "Computer science", "Computer security", "Engineering", "World Wide Web", "Geography" ], "cited_by_count": 86, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2021.3138432" }, { "id": "https://openalex.org/W2894758515", "doi": "10.1002/net.21847", "title": "Drone delivery from trucks: Drone scheduling for given truck routes", "year": 2018, "publication_date": "2018-10-04", "type": "article", "language": "en", "authors": [ "Nils Boysen", "Dirk Briskorn", "Stefan Fedtke", "Stefan Schwerdfeger" ], "first_author": "Nils Boysen", "venue": "Networks", "publisher": "Wiley", "abstract": "Last mile deliveries with unmanned aerial vehicles (also denoted as drones) are seen as one promising idea to reduce excessive road traffic. To overcome the difficulties caused by the comparatively short operating ranges of drones, an innovative concept suggests to apply trucks as mobile landing and take‐off platforms. In this context, the paper on hand schedules the delivery to customers by drones for given truck routes. Given a fixed sequence of stops constituting a truck route and a set of customers to be supplied, we aim at a drone schedule (i.e., a set of trips each defining a drone's take‐off and landing stop and the customer serviced), such that all customers are supplied and the total duration of the delivery tour is minimized. We differentiate whether multiple drones or just a single one are placed on a truck and whether or not take‐off and landing stops have to be identical. We provide an analysis of computational complexity for each resulting subproblem, introduce efficient mixed‐integer programs, and compare all cases with regard to their potential of reducing the delivery effort on the last mile.", "keywords": [ "Drone", "Truck", "Computer science", "Context (archaeology)", "Scheduling (production processes)", "Schedule", "Last mile (transportation)", "Operations research", "Transport engineering", "Mile", "Engineering", "Operations management" ], "cited_by_count": 226, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/net.21847" }, { "id": "https://openalex.org/W2889618942", "doi": "10.1109/icuas.2019.8798337", "title": "The Urban Last Mile Problem: Autonomous Drone Delivery to Your Balcony", "year": 2019, "publication_date": "2019-06-01", "type": "conference-paper", "language": "en", "authors": [ "Gino Brunner", "Bence Szebedy", "Simon Tanner", "Roger P. Wattenhofer" ], "first_author": "Gino Brunner", "venue": null, "publisher": null, "abstract": "Drone delivery has been a hot topic in the industry in the past few years. However, existing approaches either focus on rural areas or rely on centralized drop-off locations from where the last mile delivery is performed. In this paper we tackle the problem of autonomous last mile delivery in urban environments using an off-the-shelf drone. We build a prototype system that is able to fly to the approximate delivery location using GPS and then find the exact drop-off location using visual navigation. The drop-off location could, e.g., be on a balcony or porch, and simply needs to be indicated by a visual marker on the wall or window. We test our system components in simulated environments, including the visual navigation and collision avoidance. Finally, we deploy our drone in a real-world environment and show how it can find the drop-off point on a balcony. To stimulate future research in this topic we open source our code.", "keywords": [ "Drone", "Mile", "Global Positioning System", "Last mile (transportation)", "Computer science", "Real-time computing", "Window (computing)", "Point of interest", "Vanishing point", "Simulation", "Aeronautics", "Geography" ], "cited_by_count": 86, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1809.08022" }, { "id": "https://openalex.org/W2972055356", "doi": "10.1109/jiot.2019.2939397", "title": "Routing and Scheduling for Hybrid Truck-Drone Collaborative Parcel Delivery With Independent and Truck-Carried Drones", "year": 2019, "publication_date": "2019-09-04", "type": "article", "language": "en", "authors": [ "Desheng Wang", "Peng Fei Hu", "Jingxuan Du", "Pan Zhou", "Tianping Deng", "Menglan Hu" ], "first_author": "Desheng Wang", "venue": "IEEE Internet of Things Journal", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The enabling Internet-of-Things (IoT) technology has inspired a large number of novel platforms and applications. One popular IoT platform is unmanned aerial vehicles (UAVs, also known as drone). Benefiting from the intrinsic flexibility, convenience, and low cost, UAVs have great potentials to be utilized in various civil applications, including parcel delivery. However, suffering from limited payloads and battery capacities, it is uneconomical for UAVs to perform parcel delivery tasks independently. To conquer the drawbacks of low payloads and battery capacities, people propose to employ both trucks and drones to construct truck-drone parcel delivery systems. However, previous works only leverage either independent drones or truck-carried drones to collaborate with trucks. In contrast, in this article we propose to simultaneously employ trucks, truck-carried drones, and independent drones to construct a more efficient truck-drone parcel delivery system. We claim that such a hybrid parcel delivery system can fully exploit the complementary benefits of the three platforms. We propose a novel routing and scheduling algorithm, referred to as hybrid truck-drone delivery (HTDD) algorithm, to solve the hybrid parcel delivery problem, wherein M drones carried by M trucks, together with N independent drones, cooperate to deliver parcels to customers distributed in a wide region. The experimental results show that our algorithm outperforms the existing solutions which employ either independent drones or truck-carried drones.", "keywords": [ "Drone", "Truck", "Computer science", "Scheduling (production processes)", "Exploit", "Leverage (statistics)", "Computer network", "Computer security", "Engineering", "Artificial intelligence", "Automotive engineering" ], "cited_by_count": 221, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/jiot.2019.2939397" }, { "id": "https://openalex.org/W2765355161", "doi": "10.1007/978-3-319-67308-0_56", "title": "Last-Mile Deliveries by Using Drones and Classical Vehicles", "year": 2017, "publication_date": "2017-01-01", "type": "conference-paper", "language": "en", "authors": [ "Luigi Di Puglia Pugliese", "Francesca Guerriero" ], "first_author": "Luigi Di Puglia Pugliese", "venue": "Springer proceedings in mathematics & statistics", "publisher": "Springer International Publishing", "abstract": null, "keywords": [ "Drone", "Truck", "Last mile (transportation)", "Computer science", "Process (computing)", "Operations research", "Service (business)", "Aeronautics", "Mile", "Transport engineering", "Engineering", "Real-time computing" ], "cited_by_count": 106, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-319-67308-0_56" }, { "id": "https://openalex.org/W2245682929", "doi": "10.1016/j.trc.2017.11.015", "title": "On the min-cost Traveling Salesman Problem with Drone", "year": 2017, "publication_date": "2017-12-22", "type": "article", "language": "en", "authors": [ "Quang Minh Ha", "Yves Deville", "Quang Dung Pham", "Minh Hoàng Hà" ], "first_author": "Quang Minh Ha", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Travelling salesman problem", "Drone", "Computer science", "Traveling purchaser problem", "2-opt", "Mathematical optimization", "Mathematics", "Biology", "Algorithm" ], "cited_by_count": 628, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/1509.08764" }, { "id": "https://openalex.org/W4280603531", "doi": "10.1080/23311975.2022.2074340", "title": "Will customers adopt last-mile drone delivery services? An analysis of drone delivery in the emerging market economy", "year": 2022, "publication_date": "2022-05-19", "type": "article", "language": "en", "authors": [ "Charlie Chen", "Steve M. Leon", "Peter Ractham" ], "first_author": "Charlie Chen", "venue": "Cogent Business & Management", "publisher": "Cogent OA", "abstract": "Drone delivery services are novelty concepts to most people in emerging market economies. To gain competitive advantages, retailers in emerging market need to be proactive in understanding the key factors contributing to the acceptance of last-mile drone delivery services by general users. This study offers personal and social perspectives of the adoption of drone delivery services by Thai users. A total of 391 respondents participated in an online survey. The PLS-SEM method was used to perform the data analysis. The analysis results show that personal innovativeness and opinion passions are antecedents for Thai users’ perceived ease of use. However, these two antecedents do not affect Thai users’ perceived usefulness for drone delivery services. In addition, perceived privacy risk has a negative moderating effect on the relationship between PEOU and the adoption of drone delivery services. In contrast, Thai users’ perceived privacy risk has no significant moderating effect on the relationship between PU and the intention to adopt drone delivery services. Lastly, PEOU has a significant positive effect on the intention of users to adopt drone delivery services, whereas PU does not have any significant effect. These findings provide theoretical and practical implications on the moderating effect of perceived privacy risks on the relationships between perceptions and the intention to adopt the last-mile drone delivery service.", "keywords": [ "Drone", "Business", "Marketing", "Risk perception", "Last mile (transportation)", "Service (business)", "Emerging markets", "Advertising", "Internet privacy", "Perception", "Psychology", "Mile" ], "cited_by_count": 67, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.tandfonline.com/doi/pdf/10.1080/23311975.2022.2074340?needAccess=true" }, { "id": "https://openalex.org/W2996999140", "doi": "10.1016/j.trd.2019.102209", "title": "Comparison of energy demands of drone-based and ground-based parcel delivery services", "year": 2019, "publication_date": "2019-12-27", "type": "article", "language": "en", "authors": [ "Thomas Kirschstein" ], "first_author": "Thomas Kirschstein", "venue": "Transportation Research Part D Transport and Environment", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Flexibility (engineering)", "Transport engineering", "Last mile (transportation)", "Energy consumption", "Business", "Computer science", "Engineering", "Automotive engineering", "Mile" ], "cited_by_count": 262, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trd.2019.102209" }, { "id": "https://openalex.org/W3084064394", "doi": "10.1016/j.trc.2020.102762", "title": "Drone-aided routing: A literature review", "year": 2020, "publication_date": "2020-09-07", "type": "article", "language": "en", "authors": [ "Giusy Macrina", "Luigi Di Puglia Pugliese", "Francesca Guerriero", "Gilbert Laporte" ], "first_author": "Giusy Macrina", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Context (archaeology)", "Routing (electronic design automation)", "Computer science", "Focus (optics)", "Work (physics)", "Engineering", "Transport engineering", "Geography", "Computer network" ], "cited_by_count": 524, "is_retracted": false, "is_paratext": false, "open_access_url": "https://purehost.bath.ac.uk/ws/files/221385593/4._Survey_VRP_D_Copy_1_.pdf" }, { "id": "https://openalex.org/W3048667086", "doi": "10.1016/j.trd.2020.102480", "title": "The impact of airspace regulations on unmanned aerial vehicles in last-mile operation", "year": 2020, "publication_date": "2020-08-11", "type": "article", "language": "en", "authors": [ "Mo ElSayed", "Moataz Mohamed" ], "first_author": "Mo ElSayed", "venue": "Transportation Research Part D Transport and Environment", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Mile", "Electricity", "Last mile (transportation)", "Greenhouse gas", "Drone", "Diesel fuel", "Transport engineering", "Automotive engineering", "Environmental science", "Engineering", "Aeronautics", "Geography" ], "cited_by_count": 78, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trd.2020.102480" }, { "id": "https://openalex.org/W4211227202", "doi": "10.3390/su14031766", "title": "The Use of Drones for Last-Mile Delivery: A Numerical Case Study in Milan, Italy", "year": 2022, "publication_date": "2022-02-03", "type": "article", "language": "en", "authors": [ "Fabio Borghetti", "Claudia Caballini", "Angela Carboni", "Gaia Grossato", "Roberto Maja", "Benedetto Barabino" ], "first_author": "Fabio Borghetti", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The increasing use of e-commerce introduces major challenges for last-mile delivery, which is critical to ensure smooth functioning of supply chains. Besides the speed and cost of delivery, which are the most important factors for last-mile logistics, environmental and social sustainability factors are taking on an increasingly important role, especially in urban areas. In this perspective, last-mile delivery by drones could be a good choice both in terms of transport speed and sustainability. Being electrically powered, drones can reduce environmental impact; moreover, they enable the reduction of road congestion since they do not interfere with land infrastructures. The goal of this study is to analyse the viability of drones for last-mile delivery in the Italian city of Milan. A stated preference survey was carried out to assess end-user propensity towards drones. Using these results, a goods delivery service by drones was designed. Furthermore, a preliminary financial analysis was performed to evaluate the benefits for a company that would provide such a transport service. Findings show that last-mile delivery by drones can be successfully used to deliver small and light packages, reducing environmental and social impacts, and ensuring profits for the transport provider.", "keywords": [ "Last mile (transportation)", "Drone", "Mile", "Sustainability", "Business", "Service (business)", "Service provider", "Transport engineering", "Environmental economics", "Marketing", "Engineering", "Geography" ], "cited_by_count": 124, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/14/3/1766/pdf?version=1644316436" }, { "id": "https://openalex.org/W2990557569", "doi": "10.1109/mc.2019.2942290", "title": "Practical Drone Delivery", "year": 2019, "publication_date": "2019-11-21", "type": "article", "language": "en", "authors": [ "Eitan Frachtenberg" ], "first_author": "Eitan Frachtenberg", "venue": "Computer", "publisher": "IEEE Computer Society", "abstract": "Despite its enormous economic impact, the parcel delivery industry has evolved slowly over the decades with the biggest innovations coming from GPS and planning algorithms. New developments in the technologies of drone delivery, such as aircraft design, battery improvements, and control software, could transform this industry and, consequently, society as a whole.", "keywords": [ "Drone", "Computer science", "Global Positioning System", "Software", "Control (management)", "Systems engineering", "Telecommunications", "Engineering", "Artificial intelligence" ], "cited_by_count": 134, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/2/8909909/08909916.pdf" }, { "id": "https://openalex.org/W3041056939", "doi": "10.1016/j.trd.2020.102443", "title": "Carbon emissions reductions in last mile and grocery deliveries utilizing air and ground autonomous vehicles", "year": 2020, "publication_date": "2020-07-08", "type": "article", "language": "en", "authors": [ "Miguel Figliozzi" ], "first_author": "Miguel Figliozzi", "venue": "Transportation Research Part D Transport and Environment", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Automotive engineering", "Last mile (transportation)", "Service (business)", "Drone", "Electric vehicle", "Transport engineering", "Engineering", "Mile", "Business", "Marketing" ], "cited_by_count": 249, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/7341048" }, { "id": "https://openalex.org/W2908897238", "doi": "10.1109/ieem.2018.8607829", "title": "Drone-delivery Using Autonomous Mobility: An Innovative Approach to Future Last-mile Delivery Problems", "year": 2018, "publication_date": "2018-12-01", "type": "conference-paper", "language": "en", "authors": [ "Hye-Min Yoo", "Stanislav M. Chankov" ], "first_author": "Hye-Min Yoo", "venue": null, "publisher": null, "abstract": "Drone-delivery is seen as a possible solution to future last-mile delivery problems. Meanwhile, autonomous mobility allows dynamic human transportation within a city, which solves future traffic complications. The purpose of this paper is to propose an innovative delivery concept called Drone-delivery using Autonomous Mobility (DDAM). DDAM combines drone-delivery with autonomous mobility, to simultaneously solve three problems of the future cities: (1) high demand of delivery (2) short delivery lead-time and (3) complex traffic congestions. Using the Design Science Research Guideline the concept is illustrated and evaluated based on interviews with experts from relevant industries. The results indicate that the DDAM concept is more feasible as an alternative delivery method in high-demand seasons. The research reveals a high-potential for utilizing autonomous mobility in last-mile delivery.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "Food delivery", "Computer science", "Delivery system", "Transport engineering", "Risk analysis (engineering)", "Operations research", "Engineering", "Business" ], "cited_by_count": 74, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/ieem.2018.8607829" }, { "id": "https://openalex.org/W3049753201", "doi": "10.1016/j.tre.2020.102049", "title": "Optimization and analysis of a robot-assisted last mile delivery system", "year": 2020, "publication_date": "2020-08-14", "type": "article", "language": "en", "authors": [ "Michele D. Simoni", "Erhan Kutanoğlu", "Christian G. Claudel" ], "first_author": "Michele D. Simoni", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Truck", "Robot", "Computer science", "Heuristic", "Delivery Performance", "Scheduling (production processes)", "Drone", "Transport engineering", "Operations research", "Engineering", "Operations management", "Industrial engineering" ], "cited_by_count": 200, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2020.102049" }, { "id": "https://openalex.org/W4383163325", "doi": "10.1016/j.engappai.2023.106631", "title": "Sustainable last mile parcel delivery and return service using drones", "year": 2023, "publication_date": "2023-07-03", "type": "article", "language": "en", "authors": [ "Nawin Yanpirat", "Daniel F. Silva", "Alice E. Smith" ], "first_author": "Nawin Yanpirat", "venue": "Engineering Applications of Artificial Intelligence", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Truck", "Last mile (transportation)", "Travelling salesman problem", "Operations research", "Service (business)", "Vehicle routing problem", "Python (programming language)", "Mile", "Routing (electronic design automation)", "Computer network" ], "cited_by_count": 51, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.engappai.2023.106631" }, { "id": "https://openalex.org/W4200157265", "doi": "10.1016/j.jretconser.2021.102865", "title": "Critical factors characterizing consumers’ intentions to use drones for last-mile delivery: Does delivery risk matter?", "year": 2021, "publication_date": "2021-12-08", "type": "article", "language": "en", "authors": [ "Christian Nedu Osakwe", "Marek Hudík", "David Říha", "Michael Stros", "T. Ramayah" ], "first_author": "Christian Nedu Osakwe", "venue": "Journal of Retailing and Consumer Services", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Expectancy theory", "Marketing", "Social cognitive theory", "Unified theory of acceptance and use of technology", "Cognition", "Business", "Recreation", "Psychology", "Outcome (game theory)", "Consumer behaviour", "Advertising" ], "cited_by_count": 132, "is_retracted": false, "is_paratext": false, "open_access_url": "https://repository.up.ac.za/bitstream/2263/84179/1/Osakwe_Critical_2022.pdf" }, { "id": "https://openalex.org/W4294724286", "doi": "10.1016/j.cor.2022.106015", "title": "A last-mile drone-assisted one-to-one pickup and delivery problem with multi-visit drone trips", "year": 2022, "publication_date": "2022-09-06", "type": "article", "language": "en", "authors": [ "Zhihao Luo", "Ruixue Gu", "Mark Poon", "Zhong Liu", "Andrew E. B. Lim" ], "first_author": "Zhihao Luo", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Pickup", "Payload (computing)", "Truck", "Last mile (transportation)", "TRIPS architecture", "Mile", "Operations research", "Real-time computing", "Engineering", "Artificial intelligence" ], "cited_by_count": 97, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cor.2022.106015" }, { "id": "https://openalex.org/W2927378423", "doi": "10.1016/j.trc.2019.02.018", "title": "An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones", "year": 2019, "publication_date": "2019-03-22", "type": "article", "language": "en", "authors": [ "David Sacramento", "David Pisinger", "Stefan Røpke" ], "first_author": "David Sacramento", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Truck", "Vehicle routing problem", "Computer science", "Metaheuristic", "Routing (electronic design automation)", "Operations research", "2-opt", "Transport engineering", "Mathematical optimization", "Engineering" ], "cited_by_count": 566, "is_retracted": false, "is_paratext": false, "open_access_url": "https://orbit.dtu.dk/en/publications/de5c7fac-a4e0-41fc-b8e8-2f3bcb033b2b" }, { "id": "https://openalex.org/W2746411854", "doi": "10.1155/2017/3296874", "title": "A Review of Deep Learning Methods and Applications for Unmanned Aerial Vehicles", "year": 2017, "publication_date": "2017-01-01", "type": "article", "language": "en", "authors": [ "Adrián Carrio", "Carlos Sampedro", "Alejandro Rodríguez-Ramos", "Pascual Campoy" ], "first_author": "Adrián Carrio", "venue": "Journal of Sensors", "publisher": "Hindawi Publishing Corporation", "abstract": "Deep learning is recently showing outstanding results for solving a wide variety of robotic tasks in the areas of perception, planning, localization, and control. Its excellent capabilities for learning representations from the complex data acquired in real environments make it extremely suitable for many kinds of autonomous robotic applications. In parallel, Unmanned Aerial Vehicles (UAVs) are currently being extensively applied for several types of civilian tasks in applications going from security, surveillance, and disaster rescue to parcel delivery or warehouse management. In this paper, a thorough review has been performed on recent reported uses and applications of deep learning for UAVs, including the most relevant developments as well as their performances and limitations. In addition, a detailed explanation of the main deep learning techniques is provided. We conclude with a description of the main challenges for the application of deep learning for UAV-based solutions.", "keywords": [ "Deep learning", "Variety (cybernetics)", "Artificial intelligence", "Computer science", "Systems engineering", "Human–computer interaction", "Engineering" ], "cited_by_count": 372, "is_retracted": false, "is_paratext": false, "open_access_url": "http://downloads.hindawi.com/journals/js/2017/3296874.pdf" }, { "id": "https://openalex.org/W4407844915", "doi": "10.3390/drones9030158", "title": "A Review of Last-Mile Delivery Optimization: Strategies, Technologies, Drone Integration, and Future Trends", "year": 2025, "publication_date": "2025-02-21", "type": "article", "language": "en", "authors": [ "Abdullahi Sani Shuaibu", "Ashraf Mahmoud", "Tarek Sheltami" ], "first_author": "Abdullahi Sani Shuaibu", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Last-mile delivery (LMD) is an important aspect of contemporary logistics that directly affects operational cost, efficiency, and customer satisfaction. In this paper, we provide a review of the optimization techniques of LMD, focusing on Artificial Intelligence (AI) driven decision-making, IoT-supported real-time monitoring, and hybrid delivery networks. The combination of AI and IoT improves predictive analytics, dynamic routing, and fleet management, but scalability and regulatory issues are still major concerns. Hybrid frameworks that integrate drones or Unmanned Aerial Vehicles (UAVs), ground robots, and conventional vehicles reduce energy expenditure and increase delivery range, especially in urban contexts. Furthermore, sustainable logistics approaches, including electric vehicle fleets and shared delivery infrastructures, provide promise for minimizing environmental impact. However, economic viability, legal frameworks, and infrastructure readiness still influence the feasibility of large-scale adoption. This review offers a perspective on the changing patterns in LMD, calling for regulatory evolution, technological advancement, as well as interdisciplinary approaches toward cost-effective, durable, and environmentally friendly logistics systems.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Computer science", "Aeronautics", "Engineering", "Geography", "Biology", "Geodesy" ], "cited_by_count": 96, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3390/drones9030158" }, { "id": "https://openalex.org/W3015829695", "doi": "10.1016/j.promfg.2020.02.043", "title": "Using drones for parcels delivery process", "year": 2020, "publication_date": "2020-01-01", "type": "article", "language": "en", "authors": [ "Luigi Di Puglia Pugliese", "Francesca Guerriero", "Giusy Macrina" ], "first_author": "Luigi Di Puglia Pugliese", "venue": "Procedia Manufacturing", "publisher": "Elsevier BV", "abstract": "Parcels delivery is the most expensive phase of the distribution logistics. Everyday, several vehicles, usually internal combustion engine vehicles, have to serve a high number of customers spatially distributed in an urban area. Their presence generates several negative externalities, such as, noise, congestion and pollutant emissions. Drones have become a valid alternative to support the delivery process and several big companies, such as, Amazon and DHL, have started to use them for parcels deliveries. On the one hand, drones drastically reduce negative externalities, allowing a more sustainable delivery process. On the other hand, several technical aspects must be carefully taken into account. In particular, they have a limited flight endurance and capacity. In addition, several restrictions related to safety and flight area must be considered. Indeed, not all countries allow the use of drones in the urban area. In this work, we provide a qualitative and quantitative analysis on benefits and drawbacks in using drones in the parcels delivery process. We analyze three different transportation systems with incremental use of drones for the delivery. In particular, we address the problem of delivering parcels without drone, known as vehicle routing problem, the problem in which the deliveries are performed by a fleet of drones starting from the central depot, and a hybrid transportation system where the classical vehicles are equipped with drones. In the latter case, the classical vehicles perform the deliveries and the drones can get in charge some deliveries. The drone takes off from the vehicle, carries out the delivery, and lands to the same vehicle at a randevouz-location. During the drone delivery, the classical vehicle continues its work. The three transportation systems are formalized via mathematical programming models. The solutions obtained by solving the models via a general-purpose solver are compared and insights on the use of drones in the urban area are provided.", "keywords": [ "Drone", "Process (computing)", "Externality", "Work (physics)", "Transport engineering", "Vehicle routing problem", "Computer science", "Routing (electronic design automation)", "Engineering", "Economics" ], "cited_by_count": 118, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2351978920305928/pdf" }, { "id": "https://openalex.org/W3193596395", "doi": "10.1109/access.2021.3104963", "title": "The Rise of Drones in Internet of Things: A Survey on the Evolution, Prospects and Challenges of Unmanned Aerial Vehicles", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Nader Samir Labib", "Matthias R. Brust", "Grégoire Danoy", "Pascal Bouvry" ], "first_author": "Nader Samir Labib", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The recent years have seen a rise in the incorporation and integration of new smart connected devices and platforms such as Unmanned Aerial Vehicles (UAVs) to the ubiquitous network of Internet of Things (IoT). UAVs not only offer new means of delivering value-added IoT services through a wide range of applications ranging from monitoring and surveillance to on-demand last-mile delivery and people transport, but they also promise a pragmatic solution to the limitations of fixed terrestrial IoT infrastructure. Owning to their potential, UAVs are expected to soon be an integral part of our cities, dominating the shared low-altitude airspace. This introduces new research challenges in privacy, security and most notably in the safe management of UAVs’ operation under high traffic demands. To this end, this work presents a holistic study on the current state-of-the-art of UAVs and low-altitude airspace traffic management. This work additionally explores the technical standardisation landscape and highlights synergies between scientific research and standardisation efforts towards enabling safe UAV operations, while taking into consideration additional IoT inherent challenges such as security, data protection and privacy.", "keywords": [ "Drone", "Internet of Things", "Computer security", "Computer science", "Work (physics)", "The Internet", "Last mile (transportation)", "Mile", "Engineering", "Geography", "World Wide Web" ], "cited_by_count": 135, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/6514899/09514555.pdf" }, { "id": "https://openalex.org/W4411096401", "doi": "10.3390/drones9060413", "title": "Unmanned Aerial Vehicles in Last-Mile Parcel Delivery: A State-of-the-Art Review", "year": 2025, "publication_date": "2025-06-06", "type": "article", "language": "en", "authors": [ "Almodather Mohamed", "Moataz Mohamed" ], "first_author": "Almodather Mohamed", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Unmanned Aerial Vehicles (UAVs) are being increasingly implemented in parcel delivery applications. The scientific progress in this field is progressing exponentially. However, there is a notable gap in synthesizing recent research progress in UAV applications for last-mile delivery. This review study addresses this gap and conducts an in-depth review of UAV research for last-mile delivery across seven domains: environmental performance, economic impacts, social impacts, policy and regulations, routing and scheduling, charging infrastructure, and energy consumption. The review indicates that UAVs promise to reduce last-mile delivery emissions by 71% and costs by 96.5% compared to truck delivery. Saturated knowledge analysis is conducted across the seven domains to identify potential research gaps. Additionally, this review identifies key knowledge gaps, including variability in environmental and cost data, limitations associated with 2D modelling, and a lack of experimental validation. Future research interventions aimed at advancing UAV adoption in last-mile delivery applications are discussed.", "keywords": [ "Mile", "Last mile (transportation)", "State (computer science)", "Aeronautics", "Drone", "Environmental science", "Marine engineering", "Computer science", "Engineering", "Geography", "Geodesy" ], "cited_by_count": 36, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/9/6/413/pdf?version=1749201995" }, { "id": "https://openalex.org/W3117135908", "doi": "10.1002/net.22015", "title": "Trucks and drones cooperation in the last‐mile delivery process", "year": 2020, "publication_date": "2020-12-24", "type": "article", "language": "en", "authors": [ "Luigi Di Puglia Pugliese", "Giusy Macrina", "Francesca Guerriero" ], "first_author": "Luigi Di Puglia Pugliese", "venue": "Networks", "publisher": "Wiley", "abstract": "Abstract We address the problem of routing a fleet of trucks equipped with unmanned aerial vehicles, commonly known as drones, to perform deliveries in last‐mile delivery process. The customers can be served by either a truck or a drone within the respective time window of each. Each capacitated truck carries drones that can be launched to perform deliveries. The drone takes off from a truck located either at a customer or at the depot and it must land on the same truck after visiting a customer to be served. The aim is to serve all customers at minimum cost, under time window, capacity, and flying endurance constraints. We formulate the problem as a mixed integer linear program (MILP) and develop a heuristic procedure where a two‐phase strategy is embedded in a multi‐start framework. The computational results are carried out on instances generated by starting from vehicle routing problem with time windows benchmarks. We analyze the behavior of the considered transportation system by mean of the solutions provided by the MILP. The proposed formulation is able to solve instances with up to 15 customers. The solutions of the MILP are used as benchmark to assess the effectiveness of the proposed heuristic procedure.", "keywords": [ "Truck", "Drone", "Vehicle routing problem", "Computer science", "Benchmark (surveying)", "Heuristic", "Last mile (transportation)", "Integer programming", "Process (computing)", "Routing (electronic design automation)", "Integer (computer science)", "Linear programming" ], "cited_by_count": 56, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1002/net.22015" }, { "id": "https://openalex.org/W4391748388", "doi": "10.1108/ijlm-04-2023-0149", "title": "Drones in last-mile delivery: a systematic literature review from a logistics management perspective", "year": 2024, "publication_date": "2024-02-12", "type": "review", "language": "en", "authors": [ "Amer Jazairy", "Emil Persson", "Mazen Brho", "Robin von Haartman", "Per Hilletofth" ], "first_author": "Amer Jazairy", "venue": "The International Journal of Logistics Management", "publisher": "Emerald Publishing Limited", "abstract": "Purpose This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field. Design/methodology/approach Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field. Findings The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified. Research limitations/implications This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved. Practical implications The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries. Originality/value This is one of the first SLRs on drone applications in LMD from a logistics management perspective.", "keywords": [ "Drone", "Originality", "Last mile (transportation)", "Stakeholder", "Perspective (graphical)", "Systematic review", "Process (computing)", "Field (mathematics)", "Process management", "Relation (database)", "Knowledge management", "Business" ], "cited_by_count": 84, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hig.diva-portal.org/smash/get/diva2:1838692/FULLTEXT01" }, { "id": "https://openalex.org/W3122711124", "doi": "10.1109/tsmc.2020.2968839", "title": "Two-Echelon Routing Problem for Parcel Delivery by Cooperated Truck and Drone", "year": 2020, "publication_date": "2020-02-10", "type": "article", "language": "en", "authors": [ "Yao Liu", "Zhong Liu", "Jianmai Shi", "Guohua Wu", "Witold Pedrycz" ], "first_author": "Yao Liu", "venue": "IEEE Transactions on Systems Man and Cybernetics Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "A new variant of the 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 modeling 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 integrated with Tabu search, to improve the quality of the solution as well as 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", "Routing (electronic design automation)", "Vehicle routing problem", "Computer science", "Operations research", "Business", "Engineering", "Computer network", "Automotive engineering" ], "cited_by_count": 176, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tsmc.2020.2968839" }, { "id": "https://openalex.org/W2936641013", "doi": "10.1109/access.2019.2910134", "title": "A Hybrid Genetic Algorithm on Routing and Scheduling for Vehicle-Assisted Multi-Drone Parcel Delivery", "year": 2019, "publication_date": "2019-01-01", "type": "article", "language": "en", "authors": [ "Kai Peng", "Jingxuan Du", "Fang Lu", "Qianguo Sun", "Yan Dong", "Pan Zhou", "Menglan Hu" ], "first_author": "Kai Peng", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "In recent years, the unmanned aerial vehicles (UAVs) have exhibited significant market potential to greatly reduce the cost and time in the field of logistics. The use of UAVs to provide commercial courier has become an emerging industry, remarkably shifting the energy use of the freight sector. However, due to limited battery capacities, the flight duration of civilian rotorcraft UAVs is still short, hindering them from performing remote jobs. In this case, people customarily utilize ground vehicles to carry and assist UAVs in various applications, including cargo delivery. Most previous studies on vehicle-drone cooperative parcel delivery considered only one UAV, thereby suffering from low efficiency when serving a large number of customers. In this paper, we propose a novel hybrid genetic algorithm, which supports the cooperation of a ground vehicle and multiple UAVs for efficient parcel delivery. Our routing and scheduling algorithm allows multiple UAVs carried by the vehicle to simultaneously deliver multiple parcels to customers residing in different locations. The proposed algorithm consists of a pipeline of several modules: population management, heuristic population initialization, and population education. The performance evaluation results show that the proposed algorithm has significant efficiency over existing algorithms.", "keywords": [ "Drone", "Computer science", "Population", "Scheduling (production processes)", "Genetic algorithm", "Initialization", "Vehicle routing problem", "Real-time computing", "Heuristic", "Routing (electronic design automation)", "Engineering", "Computer network" ], "cited_by_count": 175, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/8600701/08692362.pdf" }, { "id": "https://openalex.org/W2567288011", "doi": "10.2148/benv.42.4.617", "title": "The Possible Impact of 3D Printing and Drones on Last-Mile Logistics: An Exploratory Study", "year": 2016, "publication_date": "2016-12-01", "type": "article", "language": "en", "authors": [ "Alan Campbell McKinnon" ], "first_author": "Alan Campbell McKinnon", "venue": "Built Environment", "publisher": "Alexandrine Press", "abstract": null, "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Exploratory research", "Engineering", "Aeronautics", "Business", "Operations management", "Architectural engineering", "Transport engineering", "Geography", "Sociology" ], "cited_by_count": 75, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2148/benv.42.4.617" }, { "id": "https://openalex.org/W2944128823", "doi": "10.1007/s10846-019-01034-w", "title": "Drone Delivery Scheduling Optimization Considering Payload-induced Battery Consumption Rates", "year": 2019, "publication_date": "2019-05-10", "type": "article", "language": "en", "authors": [ "Maryam Torabbeigi", "Gino J. Lim", "Seonjin Kim" ], "first_author": "Maryam Torabbeigi", "venue": "Journal of Intelligent & Robotic Systems", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Payload (computing)", "Drone", "Scheduling (production processes)", "Integer programming", "Schedule", "Linear programming", "Mathematical optimization", "Computer science", "Operations research", "Engineering", "Reliability engineering", "Computer network" ], "cited_by_count": 171, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10846-019-01034-w" }, { "id": "https://openalex.org/W2415513154", "doi": "10.13140/rg.2.2.24444.56962", "title": "Optimization of drone-assisted parcel delivery", "year": 2016, "publication_date": "2016-01-01", "type": "article", "language": "en", "authors": [ "Andrea Ponza" ], "first_author": "Andrea Ponza", "venue": null, "publisher": null, "abstract": null, "keywords": [ "Drone", "Computer science", "Aeronautics", "Engineering", "Biology" ], "cited_by_count": 98, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.13140/rg.2.2.24444.56962" }, { "id": "https://openalex.org/W2784102161", "doi": "10.1049/iet-its.2017.0227", "title": "En route truck–drone parcel delivery for optimal vehicle routing strategies", "year": 2018, "publication_date": "2018-01-12", "type": "article", "language": "en", "authors": [ "Mario Marinelli", "Leonardo Caggiani", "Michele Ottomanelli", "Mauro Dell’Orco" ], "first_author": "Mario Marinelli", "venue": "IET Intelligent Transport Systems", "publisher": "Institution of Engineering and Technology", "abstract": "Recently, several prominent logistic companies in Europe and the USA are seriously considering the idea of using drones launched from trucks and working in parallel to deliver packages. In the relevant literature, a novel problem formulation called travelling salesman problem with drone has been introduced, and some modelling and solution approaches have been presented. Existing approaches are based on the main assumption that the truck can dispatch and pick up a drone only at a node, i.e. the depot or a customer location. Here, the authors present a novel approach aimed to maximise the drone usage in parcel delivering. The authors consider that a truck can deliver and pick a drone up not only at a node but also along a route arc ( en route ). In this way, the operations of a drone are not strictly related to the customers’ position, but it can serve a wider area along the route. The authors tested the proposed heuristic on benchmark instances and analysed the benefits introduced with the en route approach.", "keywords": [ "Drone", "Truck", "Vehicle routing problem", "Routing (electronic design automation)", "Computer science", "Transport engineering", "Automotive engineering", "Engineering", "Computer network" ], "cited_by_count": 161, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1049/iet-its.2017.0227" }, { "id": "https://openalex.org/W2910105989", "doi": "10.1016/j.cie.2019.01.020", "title": "Multiple traveling salesman problem with drones: Mathematical model and heuristic approach", "year": 2019, "publication_date": "2019-01-10", "type": "article", "language": "en", "authors": [ "Patchara Kitjacharoenchai", "Mario Ventresca", "Mohammad Moshref‐Javadi", "Seokcheon Lee", "Jose M. A. Tanchoco", "Patrick A. Brunese" ], "first_author": "Patchara Kitjacharoenchai", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Heuristics", "Travelling salesman problem", "Computer science", "Integer programming", "Heuristic", "Operations research", "Delivery Performance", "Mathematical optimization", "Engineering", "Transport engineering" ], "cited_by_count": 406, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2019.01.020" }, { "id": "https://openalex.org/W3113241956", "doi": "10.1016/j.trc.2020.102878", "title": "Efficiency of UAV-based last-mile delivery under congestion in low-altitude air", "year": 2020, "publication_date": "2020-12-11", "type": "article", "language": "en", "authors": [ "Ruifeng She", "Yanfeng Ouyang" ], "first_author": "Ruifeng She", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Last mile (transportation)", "Transport engineering", "Flexibility (engineering)", "Computer science", "Mile", "Traffic congestion", "Energy consumption", "Automotive engineering", "Operations research", "Engineering", "Simulation" ], "cited_by_count": 98, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/am/pii/S0968090X20307786?via%3Dihub" }, { "id": "https://openalex.org/W4281255257", "doi": "10.1016/j.trd.2022.103296", "title": "Truck-based drone delivery system: An economic and environmental assessment", "year": 2022, "publication_date": "2022-05-21", "type": "article", "language": "en", "authors": [ "Andrea Baldisseri", "Chiara Siragusa", "Arianna Seghezzi", "Riccardo Mangiaracina", "Angela Tumino" ], "first_author": "Andrea Baldisseri", "venue": "Transportation Research Part D Transport and Environment", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Last mile (transportation)", "Mile", "Sustainability", "Greenhouse gas", "Automation", "Environmental economics", "Transport engineering", "Business", "Computer science", "Engineering" ], "cited_by_count": 115, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/11311/1228778" }, { "id": "https://openalex.org/W4224118409", "doi": "10.1038/s41598-022-10408-4", "title": "Drone routing problem model for last-mile delivery using the public transportation capacity as moving charging stations", "year": 2022, "publication_date": "2022-04-15", "type": "article", "language": "en", "authors": [ "Amirhossein Moadab", "Fatemeh Farajzadeh", "Omid Fatahi Valilai" ], "first_author": "Amirhossein Moadab", "venue": "Scientific Reports", "publisher": "Nature Portfolio", "abstract": "The fast and cost-efficient delivery of goods ordered online is logistically a challenging problem. Many firms are looking for ways to cut delivery times and costs by exploring opportunities to take advantage of drone technology. Deploying drones as a promising technology is more efficient from both environmental and economic perspectives in last-mile delivery. This paper considers a last-mile delivery system in which a set of drones are operated in coordination with public transportation system to deliver a set of orders to customer locations. A mathematical model based on Vehicle routing Problem (VRP) is extended to solve this problem. A real-world case inspired by Bremen 2025 transportation paradigm is also developed to validate the developed mathematical formulation. Results show that the sequence of visiting customers and public transport stations highly impacts the remaining charge and efficiency of drone tour planning. Also, using public transport vehicles, which enables drones to charge their battery or to approach customers, can reduce the number of drones required for satisfying the demands in a service area. The results show that there are high potentials to save energy for drone-enabled last-mile delivery by using the public transportation network.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "Computer science", "Routing (electronic design automation)", "Transport engineering", "Public transport", "Set (abstract data type)", "Operations research", "Computer network", "Engineering" ], "cited_by_count": 89, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.nature.com/articles/s41598-022-10408-4.pdf" }, { "id": "https://openalex.org/W4391268554", "doi": "10.1016/j.retrec.2023.101404", "title": "Consumer acceptance of drone-based technology for last mile delivery", "year": 2024, "publication_date": "2024-01-26", "type": "article", "language": "en", "authors": [ "Sebastian Schmidt", "Adriana Saraceni" ], "first_author": "Sebastian Schmidt", "venue": "Research in Transportation Economics", "publisher": "Elsevier BV", "abstract": "Drones are expected to allow faster and more efficient last mile parcel delivery while at the same time reducing relevant costs. This studies’ purpose is to understand what factors influence consumer acceptance in Germany. The Unified Theory of Acceptance and Use of Technology model was expand using an incremental approach. The construct performance expectancy was replaced with the three context-specific constructs, environmental performance expectancy, speed expectancy, and relative advantage of contact-free delivery. Four perceived risk constructs (i.e., privacy risk, safety risk, noise risk, financial risk) were added. Eleven hypotheses were developed and tested via an online survey. The data were analyzed using structural equation modeling in Statistical Package for the Social Sciences. Relative advantage of contact-free delivery, hedonic motivation, and social influence are the highlights among the factors investigated for their influence on consumer acceptance. The influence on the perceived risk constructs privacy risk and safety risk varies depending on drone usage experience and gender. The value of the study stems from the proposed extended Unified Theory of Acceptance and Use of Technology model, tailored to a new technology context (drones for last mile parcel delivery) and a different cultural setting (Germany). This research contributes to the multidisciplinary approach of existing drone research by adding a consumer perspective to the mainly logistics provider-oriented engineering, informatics, and operations research.", "keywords": [ "Expectancy theory", "Unified theory of acceptance and use of technology", "Structural equation modeling", "Drone", "Context (archaeology)", "Marketing", "Risk analysis (engineering)", "Business", "Computer science", "Psychology", "Social psychology", "Geography" ], "cited_by_count": 46, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.retrec.2023.101404" }, { "id": "https://openalex.org/W2892159790", "doi": "10.3390/su10093344", "title": "Sizing of the Drone Delivery Fleet Considering Energy Autonomy", "year": 2018, "publication_date": "2018-09-19", "type": "article", "language": "en", "authors": [ "Asma Troudi", "Sid-Ali Addouche", "Sofiène Dellagi", "Abderrahman El Mhamedi" ], "first_author": "Asma Troudi", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "One of the most innovative solutions treated in the literature in order to reduce the environmental impact of urban parcel delivery logistics is the use of drones for delivery on the last kilometer. Consequently, nowadays, the primary challenge is essentially related to the drones’ fleet sizing according to its means of support for the urban delivery of parcels. In this paper, we will discuss the issue of dimensioning from a forecast of deliveries of an urban perimeter, the size of the fleet, the stock of battery to dispose of and the strategy of battery charging. We will present an analytical model expressing the proposed problem of the optimal drones’ delivery mission taking into account the issues of autonomy and energy consumption related to the drone’s technical specification. According to the developed analytical model, two optimization policies will be proposed. The first policy consists of planning missions under reducing distance. The second policy tries to make a compromise between the distance and the number of drones. A case study will be presented in order to compare the two policies based on the overall cost of a plan. The main objective of the study is to create a decision-making tool for the design of a drone fleet in the case of forecast deliveries over a time horizon under operational constraints.", "keywords": [ "Drone", "Dimensioning", "Dispose pattern", "Operations research", "Sizing", "Computer science", "Profit (economics)", "Transport engineering", "Engineering", "Economics" ], "cited_by_count": 109, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/10/9/3344/pdf?version=1537338292" }, { "id": "https://openalex.org/W4296767464", "doi": "10.1016/j.engappai.2022.105439", "title": "Machine learning approach for truck-drones based last-mile delivery in the era of industry 4.0", "year": 2022, "publication_date": "2022-09-20", "type": "article", "language": "en", "authors": [ "Ali Arishi", "Krishna Krishnan", "Majed Arishi" ], "first_author": "Ali Arishi", "venue": "Engineering Applications of Artificial Intelligence", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Computer science", "Travelling salesman problem", "Cluster analysis", "Last mile (transportation)", "Vehicle routing problem", "Routing (electronic design automation)", "Mile", "Operations research", "Artificial intelligence", "Computer network" ], "cited_by_count": 66, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.engappai.2022.105439" }, { "id": "https://openalex.org/W4283695239", "doi": "10.1093/imaman/dpac006", "title": "Last mile logistics: Research trends and needs", "year": 2022, "publication_date": "2022-06-29", "type": "article", "language": "en", "authors": [ "Emrah Demir", "Aris A Syntetos", "Tom Van Woensel" ], "first_author": "Emrah Demir", "venue": "IMA Journal of Management Mathematics", "publisher": "Oxford University Press", "abstract": "Abstract Aspiring green agendas in conjunction with tremendous economic pressures are resulting in an increased attention to the environment and technological innovations for improving existing logistics systems. Last mile logistics, in particular, are becoming much more than a consumer convenience necessity and a transportation optimization exercise. Rather, this area presents a true opportunity to foster both financial and environmental sustainability. This paper investigates recent technological advancements and pending needs related to business and social innovations, emphasizing green logistics and city logistics concepts. We discuss various pertinent aspects, including drones, delivery robots, truck platooning, collection and pickup points, collaborative logistics, integrated transportation, decarbonization and advanced transport analytics. From a mathematical perspective, we focus on the basic features of the vehicle routing problem and some of its variants. We provide recommendations around strategies that may facilitate the adoption of new effective technologies and innovations.", "keywords": [ "Last mile (transportation)", "Drone", "Humanitarian Logistics", "Truck", "Sustainability", "Business", "Analytics", "Supply chain", "City logistics", "Mile", "Computer science", "Transport engineering" ], "cited_by_count": 78, "is_retracted": false, "is_paratext": false, "open_access_url": "https://academic.oup.com/imaman/article-pdf/33/4/549/45047530/dpac006.pdf" }, { "id": "https://openalex.org/W3150294226", "doi": "10.1145/3448079", "title": "Efficient Schedule of Energy-Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery", "year": 2021, "publication_date": "2021-03-19", "type": "article", "language": "en", "authors": [ "Yan Pan", "Shining Li", "Qianwu Chen", "Nan Zhang", "Tao Cheng", "Zhigang Li", "Bin Guo", "Qingye Han", "Ting Zhu" ], "first_author": "Yan Pan", "venue": "Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies", "publisher": "Association for Computing Machinery", "abstract": "Stimulated by the dramatical service demand in the logistics industry, logistics trucks employed in last-mile parcel delivery bring critical public concerns, such as heavy cost burden, traffic congestion and air pollution. Unmanned Aerial Vehicles (UAVs) are a promising alternative tool in last-mile delivery, which is however limited by insufficient flight range and load capacity. This paper presents an innovative energy-limited logistics UAV schedule approach using crowdsourced buses. Specifically, when one UAV delivers a parcel, it first lands on a crowdsourced social bus to parcel destination, gets recharged by the wireless recharger deployed on the bus, and then flies from the bus to the parcel destination. This novel approach not only increases the delivery range and load capacity of battery-limited UAVs, but is also much more cost-effective and environment-friendly than traditional methods. New challenges therefore emerge as the buses with spatiotemporal mobility become the bottleneck during delivery. By landing on buses, an Energy-Neutral Flight Principle and a delivery scheduling algorithm are proposed for the UAVs. Using the Energy-Neutral Flight Principle, each UAV can plan a flying path without depleting energy given buses with uncertain velocities. Besides, the delivery scheduling algorithm optimizes the delivery time and number of delivered parcels given warehouse location, logistics UAVs, parcel locations and buses. Comprehensive evaluations using a large-scale bus dataset demonstrate the superiority of the innovative logistics UAV schedule approach.", "keywords": [ "Schedule", "Last mile (transportation)", "Truck", "Transport engineering", "Bottleneck", "Computer science", "Scheduling (production processes)", "Battery capacity", "Mile", "Automotive engineering", "Engineering", "Battery (electricity)" ], "cited_by_count": 48, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1145/3448079" }, { "id": "https://openalex.org/W3167291459", "doi": "10.1109/access.2021.3087751", "title": "Unmanned Aerial Vehicle Last-Mile Delivery Considering Backhauls", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Ahram Jeon", "Joohang Kang", "Byungil Choi", "Nakyung Kim", "Joonyup Eun", "Taesu Cheong" ], "first_author": "Ahram Jeon", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Utilizing unmanned aerial vehicles for delivery service has been drawing attention in the logistics industry. Since commercial unmanned aerial vehicles have fundamental limitations on payloads and battery capacities, hybrid ground vehicle and unmanned aerial vehicle models have been actively investigated as practical solutions. However, these studies have focused on linehaul (delivery) demands, excluding a large number of backhaul (pickup) demands. If we consider both demands at the same time, an empty unmanned aerial vehicle that finished linehaul service can be immediately used to serve a backhaul customer. In this study, we investigate the differences that arise by considering backhauls as an additional element of the routing problem. A mixed integer linear programming model is developed, and a heuristic is constructed to solve large-scale problems. To demonstrate the effectiveness of our model, we compare it to existing models using a real-world example. Our solution is also evaluated based on experiments employing a large number of randomly generated datasets.", "keywords": [ "Computer science", "Backhaul (telecommunications)", "Drone", "Last mile (transportation)", "Vehicle routing problem", "Integer programming", "Pickup", "Heuristic", "Real-time computing", "Routing (electronic design automation)", "Artificial intelligence", "Mile" ], "cited_by_count": 37, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/9312710/09449931.pdf" }, { "id": "https://openalex.org/W4285296730", "doi": "10.1109/tits.2022.3181282", "title": "Collaborative Truck-Drone Routing for Contactless Parcel Delivery During the Epidemic", "year": 2022, "publication_date": "2022-06-20", "type": "article", "language": "en", "authors": [ "Guohua Wu", "Ni Mao", "Qizhang Luo", "Binjie Xu", "Jianmai Shi", "Ponnuthurai Nagaratnam Suganthan" ], "first_author": "Guohua Wu", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The COVID-19 pandemic calls for contactless deliveries. To prevent the further spread of the disease and ensure the timely delivery of supplies, this paper investigates a collaborative truck-drone routing problem for contactless parcel delivery (CRP-T&D), which allows multiple trucks and multiple drones to deliver parcels cooperatively in epidemic areas. We formulate a mixed-integer programming model that minimizes the delivery time, with the consideration of the energy consumption model of drones. To solve CRP-T&D, we develop an improved variable neighborhood descent (IVND) that combines the Metropolis acceptance criterion of Simulated Annealing (SA) and the tabu list of Tabu Search (TS). Meanwhile, the integration of K-means clustering and Nearest neighbor strategy is applied to generate the initial solution. To evaluate the performance of IVND, experiments are conducted by comparing IVND with VND, SA, TS, variants of VND, and large neighborhood search (LNS) on instances with different scales. Several critical factors are tested to verify the robustness of IVND. Moreover, the experimental results on a practical instance further demonstrate the superior performance of IVND.", "keywords": [ "Drone", "Tabu search", "Robustness (evolution)", "Computer science", "Simulated annealing", "Truck", "Vehicle routing problem", "Routing (electronic design automation)", "Cluster analysis", "Integer programming", "Computer network", "Engineering" ], "cited_by_count": 122, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2022.3181282" }, { "id": "https://openalex.org/W3016657056", "doi": "10.1109/tte.2020.2988149", "title": "A Method of Optimized Deployment of Charging Stations for Drone Delivery", "year": 2020, "publication_date": "2020-04-15", "type": "article", "language": "en", "authors": [ "Hailong Huang", "Andrey V. Savkin" ], "first_author": "Hailong Huang", "venue": "IEEE Transactions on Transportation Electrification", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Drones have become a new means for parcel delivery in recent years. As the flight distances of currently available commercial drones are usually limited due to the battery capacity constraint, this article considers the placement of charging stations to charge or replace the battery, and thus enlarge the coverage of customers. The problem of deploying a number of charging stations to cover the customers in a demand area is investigated. A computationally efficient deployment approach is proposed. It first deploys charging stations in a triangle pattern, which fully covers the demand area. Accounting the locations of customers in the area, we then use an adjustment procedure to recursively remove some charging stations that cover no or fewer customers and reposition the remaining charging stations. Computer simulations are conducted, and comparisons with an existing relevant method are demonstrated to show the effectiveness of the proposed approach.", "keywords": [ "Software deployment", "Drone", "Cover (algebra)", "Battery capacity", "Computer science", "Battery (electricity)", "Constraint (computer-aided design)", "Operations research", "Real-time computing", "Transport engineering", "Simulation", "Engineering" ], "cited_by_count": 95, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tte.2020.2988149" }, { "id": "https://openalex.org/W4283518432", "doi": "10.1016/j.trc.2022.103763", "title": "Heterogeneous multi-drone routing problem for parcel delivery", "year": 2022, "publication_date": "2022-06-25", "type": "article", "language": "en", "authors": [ "Xupeng Wen", "Guohua Wu" ], "first_author": "Xupeng Wen", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Payload (computing)", "Computer science", "Real-time computing", "Computer network" ], "cited_by_count": 88, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2022.103763" }, { "id": "https://openalex.org/W4390024498", "doi": "10.1016/j.cie.2023.109849", "title": "Cooperative trucks and drones for rural last-mile delivery with steep roads", "year": 2023, "publication_date": "2023-12-20", "type": "article", "language": "en", "authors": [ "Jiuhong Xiao", "Ying Li", "Zhiguang Cao", "Jianhua Xiao" ], "first_author": "Jiuhong Xiao", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Mile", "Truck", "Drone", "Last mile (transportation)", "Transport engineering", "Aeronautics", "Engineering", "Forensic engineering", "Business", "Geography", "Automotive engineering" ], "cited_by_count": 47, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2023.109849" }, { "id": "https://openalex.org/W3206146521", "doi": "10.3390/electronics10202510", "title": "On Optimizing a Multi-Mode Last-Mile Parcel Delivery System with Vans, Truck and Drone", "year": 2021, "publication_date": "2021-10-15", "type": "article", "language": "en", "authors": [ "Chuan Wang", "Hongjie Lan", "Francisco Saldanha‐da‐Gama", "Youhua Chen" ], "first_author": "Chuan Wang", "venue": "Electronics", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "This work focuses on the optimization of a last-mile delivery system with multiple transportation modes. In this scenario, parcels need to be delivered to each customer point. The major feature of the problem is the combination of a fleet of road vehicles (vans) with a drone. Each van visits a subset of demand nodes to be determined according to the route of the van. The drone serves the customers not served by vans. At the same time, considering the safety, policy and terrain as well as the need to replace the battery, the drone needs to be transported by truck to the identified station along with the parcel. From each such station, the drone serves a subset of customers according to a direct assignment pattern, i.e., every time the drone is launched, it serves one demand node and returns to the station to collect another parcel. Similarly, the truck is used to transport the drone and cargo between stations. This is somewhat different from the research of other scholars. In terms of the joint distribution of the drone and road vehicle, most scholars will choose the combination of two transportation tools, while we use three. The drone and vans are responsible for distribution services, and the trucks are responsible for transporting the goods and drone to the station. The goal is to optimize the total delivery cost which includes the transportation costs for the vans and the delivery cost for the drone. A fixed cost is also considered for each drone parking site corresponding to the cost of positioning the drone and using the drone station. A discrete optimization model is presented for the problem in addition to a two-phase heuristic algorithm. The results of a series of computational tests performed to assess the applicability of the model and the efficiency of the heuristic are reported. The results obtained show that nearly 10% of the cost can be saved by combining the traditional delivery mode with the use of a drone and drone stations.", "keywords": [ "Drone", "Last mile (transportation)", "Truck", "Transport engineering", "Mile", "Computer science", "Data striping", "Engineering", "Operations research", "Automotive engineering", "Geography" ], "cited_by_count": 29, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2079-9292/10/20/2510/pdf?version=1634693226" }, { "id": "https://openalex.org/W3194590737", "doi": "10.1007/s10957-021-01918-8", "title": "The Last-Mile Delivery Process with Trucks and Drones Under Uncertain Energy Consumption", "year": 2021, "publication_date": "2021-08-23", "type": "article", "language": "en", "authors": [ "Luigi Di Puglia Pugliese", "Francesca Guerriero", "Maria Grazia Scutellà" ], "first_author": "Luigi Di Puglia Pugliese", "venue": "Journal of Optimization Theory and Applications", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Truck", "Energy consumption", "Computer science", "Benchmark (surveying)", "Reliability (semiconductor)", "Process (computing)", "Operations research", "Fuel efficiency", "Mathematical optimization", "Engineering", "Automotive engineering" ], "cited_by_count": 51, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10957-021-01918-8" }, { "id": "https://openalex.org/W3188918102", "doi": "10.3390/en14164748", "title": "Selecting Freight Transportation Modes in Last-Mile Urban Distribution in Pamplona (Spain): An Option for Drone Delivery in Smart Cities", "year": 2021, "publication_date": "2021-08-04", "type": "article", "language": "en", "authors": [ "Adrián Serrano-Hernández", "Aitor Ballano", "Javier Faulín" ], "first_author": "Adrián Serrano-Hernández", "venue": "Energies", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Urban distribution in medium-sized cities faces a major challenge, mainly when deliveries are difficult in the city center due to: an increase of e-commerce, weak public transportation system, and the promotion of urban sustainability plans. As a result, private cars, public transportation, and freight transportation compete for the same space. This paper analyses the current state for freight logistics in the city center of Pamplona (Spain) and proposes alternative transportation routes and transportation modes in the last-mile city center distribution according to different criteria evaluated by residents. An analytic hierarchy process (AHP) was developed. A number of alternatives have been assessed considering routes and transportation modes: the shortest route criterion and avoiding some city center area policies are combined with traditional van-based, bike, and aerial (drone) distribution protocols for delivering parcels and bar/restaurant supplies. These alternatives have been evaluated within a multicriteria framework in which economic, environmental, and social objectives are considered at the same time. The point in this multicriteria framework is that the criteria/alternative AHP weights and priorities have been set according to a survey deployed in the city of Pamplona (Navarre, Spain). The survey and AHP results show the preference for the use of drone or bike distribution in city center in order to reduce social and environmental issues.", "keywords": [ "Analytic hierarchy process", "Transport engineering", "Public transport", "Distribution (mathematics)", "Last mile (transportation)", "Urban sprawl", "Drone", "Business", "Geography", "Urban planning", "Mile", "Engineering" ], "cited_by_count": 43, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1996-1073/14/16/4748/pdf?version=1628244040" }, { "id": "https://openalex.org/W4319064580", "doi": "10.3390/su15032774", "title": "Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda", "year": 2023, "publication_date": "2023-02-03", "type": "article", "language": "en", "authors": [ "Valeska Engesser", "Evy Rombaut", "Lieselot Vanhaverbeke", "Philippe Lebeau" ], "first_author": "Valeska Engesser", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The implementation of autonomous delivery solutions in last-mile logistics operations is considered promising. Autonomous delivery solutions can help in tackling urban challenges related to last-mile logistics operations. Urbanization creates higher mobility and transportation demand, which contributes to increased congestion levels, traffic, air pollution, and accident rates. Moreover, mega-trends, such as e-commerce, demand that logistics companies react to increased customer expectations in terms of delivery time and service. Concerning service, electrified autonomous delivery solutions have the potential to operate 24/7 and can help to overcome driver shortages. This paper conducts a systematic literature review. Based on the literature set, a snowballing procedure was applied. Complementary gray literature was included. This work discusses different autonomous delivery solutions such as Autonomous Delivery Robots (ADRs), Unmanned Aerial Vehicles (UAVs), two- or multi-tiered systems, and the concept of passenger and freight integration. The work presents advantages and disadvantages, enabling the comparison of solutions. Furthermore, a research agenda is provided, from which practical-managerial and theoretical implications can be derived. The research agenda can help researchers, manufacturers, businesses, and governmental institutions to prepare for the arrival and subsequent implementation of autonomous delivery services. Various implications related to energy demand, legislation, implementation strategy, training, and risk and safety are presented. The outcome of this work calls for collaboration among various stakeholders, encourages mutual learning, and hints at the importance of national and international development projects.", "keywords": [ "Last mile (transportation)", "Work (physics)", "Traffic congestion", "Service (business)", "Transport engineering", "Humanitarian Logistics", "Business", "Risk analysis (engineering)", "Computer science", "Process management", "Mile", "Marketing" ], "cited_by_count": 117, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/15/3/2774/pdf?version=1675415572" }, { "id": "https://openalex.org/W4293499165", "doi": "10.1109/access.2022.3202895", "title": "Hybrid Truck-Drone Delivery Systems: A Systematic Literature Review", "year": 2022, "publication_date": "2022-01-01", "type": "review", "language": "en", "authors": [ "Batool Madani", "Malick Ndiaye" ], "first_author": "Batool Madani", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Owing to the continued development of e-commerce, logisticians now have an outstanding obligation to tackle last-mile delivery challenges. A number of logistics providers have suggested the incorporation of drones with trucks to provide a more flexible delivery system. This paper analyzes the content of 95 publications related to hybrid truck-drone delivery systems (HTDDS) in the context of last-mile delivery. First, a brief overview of the potential implementation of drone delivery systems is presented, including their integration with other vehicles. The overview aims to demonstrate the operational characteristics of such systems and their implications. Then, the surveyed literature is classified based on vehicles roles, system configuration, problem formulation, and solution methods. In relation to this research, several key findings and potential research directions are discussed. Despite the high level of interest in HTDDS research, it is still in its early phases and requires improvements in various areas. The payload capacity, speed, range, and energy consumption are all factors that must be considered in the modeling of drone characteristics. Almost all studies identify customer requests before the delivery operation begins. However, customer demands for immediate delivery present an opportunity for real-time optimization to provide solutions for e-commerce activities. Environmental issues are developing, as the last-mile delivery problem is regarded as the most polluting portion of the supply chain. Thus, more consideration should be given to the environmental impact of HTDDS. Finally, research on drone routing related to air traffic management has received relatively little attention.", "keywords": [ "Drone", "Computer science", "Truck", "Engineering", "Aerospace engineering" ], "cited_by_count": 89, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/6514899/09869811.pdf" }, { "id": "https://openalex.org/W4362583780", "doi": "10.3390/logistics7020021", "title": "A Comparative Review of Air Drones (UAVs) and Delivery Bots (SUGVs) for Automated Last Mile Home Delivery", "year": 2023, "publication_date": "2023-04-03", "type": "article", "language": "en", "authors": [ "Fang Li", "Oliver Kunze" ], "first_author": "Fang Li", "venue": "Logistics", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Background: UAVs (Unmanned Aerial Vehicles) and SUGVs (Sidewalk Unmanned Ground Vehicles) are two prominent options to revolutionize last mile home delivery. However, there is no literature yet addressing a comprehensive assessment of them. To bridge this research gap, this paper aimed to compare UAVs to SUGVs in the context of urban parcel delivery from a practical, conceptual, technological, commercial, and environmental perspective. Methodology: Based on structured literature and web research, this paper provided a comparative status quo review of these two delivery concepts. We introduced a parameter-based cost calculus model to estimate the costs per shipment for each technology. To detect the key cost drivers, we applied a one-way sensitivity analysis, as well as a “full factorial design of experiment” approach. Results: These key cost drivers for both operations are the “number of vehicles per operator” and the “average beeline service radius”. From today’s commercial point of view, our model indicated better profitability of SUGVs. However, technical and regulatory developments may render different results in the future. As SUGVs emit significantly less noise than UAVs, we assume that SUGVs have an additional advantage for usage in autonomous urban last mile delivery from a resident’s perspective. Conclusions: Both key cost drivers will significantly influence the commercial viability of unmanned home delivery services. Safety and security aspects will determine regulatory rules on “number of vehicles per operator”. To increase the “average beeline service radius”, UAVs could profit from mothership delivery concepts while SUGV delivery may co-use existing public transport infrastructure.", "keywords": [ "Drone", "Last mile (transportation)", "Computer science", "Context (archaeology)", "Flexibility (engineering)", "Transport engineering", "Computer security", "Operations research", "Engineering", "Mile" ], "cited_by_count": 41, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2305-6290/7/2/21/pdf?version=1680492468" }, { "id": "https://openalex.org/W2982191552", "doi": "10.1080/01605682.2019.1671156", "title": "Parcel delivery by vehicle and drone", "year": 2019, "publication_date": "2019-10-24", "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 single-vehicle parcel delivery problem in which customers may be served either by the vehicle or by a portable companion drone launched from the vehicle. The problem may be viewed as a Traveling Salesman Problem with Drone (TSP-D), and is modelled as a 0-1 mixed-integer program (MIP) that synchronizes vehicle and drone operations with the objective of minimizing the duration of the joint tour. Using a combination of valid inequalities, pre-processing, and other bound tightening strategies, we enhance the tractability of the proposed MIP formulation.", "keywords": [ "Drone", "Travelling salesman problem", "Computer science", "Integer programming", "Operations research", "Purchasing", "Aeronautics", "Mathematical optimization", "Engineering", "Mathematics", "Operations management", "Algorithm" ], "cited_by_count": 60, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/01605682.2019.1671156" }, { "id": "https://openalex.org/W4321457416", "doi": "10.1016/j.ejor.2023.02.030", "title": "A branch-and-price-and-cut algorithm for the truck-based drone delivery routing problem with time windows", "year": 2023, "publication_date": "2023-02-21", "type": "article", "language": "en", "authors": [ "Yunqiang Yin", "Dongwei Li", "Dujuan Wang", "Joshua Ignatius", "T.C.E. Cheng", "Sutong Wang" ], "first_author": "Yunqiang Yin", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Truck", "Drone", "Computer science", "Vehicle routing problem", "Leverage (statistics)", "Routing (electronic design automation)", "Node (physics)", "Operations research", "Mathematical optimization", "Computer network", "Engineering", "Mathematics" ], "cited_by_count": 139, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ejor.2023.02.030" }, { "id": "https://openalex.org/W3191731896", "doi": "10.1186/s12544-021-00501-6", "title": "Picture fuzzy WASPAS method for selecting last-mile delivery mode: a case study of Belgrade", "year": 2021, "publication_date": "2021-07-30", "type": "article", "language": "en", "authors": [ "Vladimir Šimić", "Dragan Lazarević", "Momčilo Đobrodolac" ], "first_author": "Vladimir Šimić", "venue": "European Transport Research Review", "publisher": "Springer Science+Business Media", "abstract": "Background: Last-mile delivery (LMD) is becoming more and more demanding due to an increasing number of users and traffic problems in cities. Besides, medical crises (like the COVID-19 outbreak) and air pollution represent additional motives for the transition from traditional to socially and environmentally sustainable LMD mode. An emerging problem for companies in the postal and logistics industry is how to determine the best LMD mode in a multi-criteria setting under uncertainty. Method: For the first time, an extension of the Weighted Aggregated Sum Product ASsessment (WASPAS) method under the picture fuzzy environment is presented to solve the LMD mode selection problem. The introduced picture fuzzy set (PFS) based multi-criteria decision-making (MCDM) method can be highly beneficial to managers who are in charge of LMD since it can take into account the neutral/refusal information and efficiently deal with high levels of imprecise, vague, and uncertain information. The comparative analysis with the existing state-of-the-art PFS-based MCDM methods approved the high reliability of the proposed picture fuzzy WASPAS method. Its high robustness and consistency are also confirmed. The presented method can be used to improve LMD in urban areas worldwide. Besides, it can be applied to solve other emerging MCDM problems in an uncertain environment. Findings: A real-life case study of Belgrade is presented to fully illustrate the potentials and applicability of the picture fuzzy WASPAS method. The results show that postomates are the best mode for LMD in Belgrade, followed by cargo bicycles, drones, traditional delivery, autonomous vehicles, and tube transport. Supplementary Information: The online version contains supplementary material available at 10.1186/s12544-021-00501-6.", "keywords": [ "Multiple-criteria decision analysis", "Computer science", "Fuzzy logic", "Consistency (knowledge bases)", "Robustness (evolution)", "Operations research", "Mode (computer interface)", "Fuzzy set", "Risk analysis (engineering)", "Business", "Engineering", "Artificial intelligence" ], "cited_by_count": 132, "is_retracted": false, "is_paratext": false, "open_access_url": "https://etrr.springeropen.com/track/pdf/10.1186/s12544-021-00501-6" }, { "id": "https://openalex.org/W2618465491", "doi": "10.1109/syscon.2017.7934790", "title": "Optimization of a modular drone delivery system", "year": 2017, "publication_date": "2017-04-01", "type": "conference-paper", "language": "en", "authors": [ "Jaihyun Lee" ], "first_author": "Jaihyun Lee", "venue": "2017 Annual IEEE International Systems Conference (SysCon)", "publisher": null, "abstract": "Drones have recently become a promising solution for rapid parcel delivery due to advances in battery technology and navigation systems. Drones have inherited limitations in battery capacity and payload, which make their efficient operation and management a critical problem for a successful delivery system. Adopting modularity in the drone design can provide operational benefits to increase overall fleet readiness and reduce overall fleet size. This paper discusses the potential value of introducing modular design to a drone delivery system. We propose an optimization method for the operation management of a fleet of modular delivery drones. This paper presents simulation results that compare the proposed method with existing operation management methods. The results show that a simple operation management strategy can make a drone delivery system unstable with increasing demand on certain types of modules in the fleet. The results comparing modular and non-modular drone operation also prove that the proposed operation management method with modular drones can save delivery time and energy consumption during a delivery operation over non-modular drones.", "keywords": [ "Drone", "Modular design", "Payload (computing)", "Computer science", "Modularity (biology)", "Systems engineering", "Reliability engineering", "Engineering", "Computer security", "Operating system" ], "cited_by_count": 69, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/syscon.2017.7934790" }, { "id": "https://openalex.org/W3027940156", "doi": "10.1109/tits.2020.2992549", "title": "Synchronized Truck and Drone Routing in Package Delivery Logistics", "year": 2020, "publication_date": "2020-05-22", "type": "article", "language": "en", "authors": [ "D DAS", "Rohan Sewani", "Junwei Wang", "Manoj Kumar Tiwari" ], "first_author": "D DAS", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The use of Unmanned Aerial Vehicles (UAVs) in delivery logistics has become an efficient solution with the advancement of autonomous robotics. This paper proposes a novel mechanism that synchronizes drones and delivery trucks; particularly the case where trucks can work as mobile launching and retrieval sites. The problem is a Vehicle Routing Problem with Time Windows and Synchronized Drones. A multi-objective optimization model is developed with two conflicting objectives, minimizing the travel costs and maximizing the customer service level in terms of timely deliveries. A novel Collaborative Pareto Ant Colony Optimization algorithm is proposed to solve the model and Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to compare and validate the proposed algorithm. The experimental results indicate that the proposed mechanism is an efficient solution to parcel delivery logistics.", "keywords": [ "Drone", "Truck", "Ant colony optimization algorithms", "Genetic algorithm", "Computer science", "Sorting", "Vehicle routing problem", "Routing (electronic design automation)", "Pareto principle", "Service (business)", "Multi-objective optimization", "Operations research" ], "cited_by_count": 231, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2020.2992549" }, { "id": "https://openalex.org/W4308351840", "doi": "10.3390/su142114473", "title": "Application of Unmanned Aerial Vehicles in Logistics: A Literature Review", "year": 2022, "publication_date": "2022-11-04", "type": "article", "language": "en", "authors": [ "Yi Li", "Min Liu", "Dandan Jiang" ], "first_author": "Yi Li", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The booming development of e-commerce has brought many challenges to the logistics industry. To ensure the sustainability of the logistics industry, the impact of environmental and social sustainability factors on logistics development needs to be considered. Unmanned Aerial Vehicles (UAVs)/drones are used in the logistics field because of their flexibility, low cost, environmental protection and energy-saving advantages, which can achieve both economic benefits and social benefits. This paper reviews 36 studies on UAVs applications in logistics from the Web of Science database from the past two years (2021–2022). The selected literature is classified into theoretical models (the traveling salesman problem and other path planning problems), application scenarios (medical safety applications and last-mile delivery problems) and other problems (UAV implementation obstacles, costs, pricing, etc.). Finally, future directions of UAVs are proposed, such as different application scenarios that can be considered and different algorithms that can be combined to optimize paths for UAVs to specific flight environments.", "keywords": [ "Flexibility (engineering)", "Drone", "Sustainability", "Travelling salesman problem", "Computer science", "Field (mathematics)", "Transport engineering", "Humanitarian Logistics", "Risk analysis (engineering)", "Operations research", "Business", "Engineering" ], "cited_by_count": 138, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/14/21/14473/pdf?version=1667547080" }, { "id": "https://openalex.org/W4391554721", "doi": "10.1016/j.ejor.2024.01.045", "title": "Fleet resupply by drones for last-mile delivery", "year": 2024, "publication_date": "2024-02-02", "type": "article", "language": "en", "authors": [ "Juan C. Pina-Pardo", "Daniel F. Silva", "Alice E. Smith", "Ricardo A. Gatica" ], "first_author": "Juan C. Pina-Pardo", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Truck", "Drone", "Computer science", "Vehicle routing problem", "Integer programming", "Operations research", "Routing (electronic design automation)", "Transport engineering", "Engineering", "Automotive engineering", "Computer network" ], "cited_by_count": 29, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ejor.2024.01.045" }, { "id": "https://openalex.org/W3128252576", "doi": "10.1287/trsc.2020.1017", "title": "Exact Methods for the Traveling Salesman Problem with Drone", "year": 2021, "publication_date": "2021-02-05", "type": "article", "language": "en", "authors": [ "Roberto Roberti", "Mario Ruthmair" ], "first_author": "Roberto Roberti", "venue": "Transportation Science", "publisher": "Institute for Operations Research and the Management Sciences", "abstract": "Efficiently handling last-mile deliveries becomes more and more important nowadays. Using drones to support classical vehicles allows improving delivery schedules as long as efficient solution methods to plan last-mile deliveries with drones are available. We study exact solution approaches for some variants of the traveling salesman problem with drone (TSP-D) in which a truck and a drone are teamed up to serve a set of customers. This combination of truck and drone can exploit the benefits of both vehicle types: the truck has a large capacity but usually low travel speed in urban areas; the drone is faster and not restricted to street networks, but its range and carrying capacity are limited. We propose a compact mixed-integer linear program (MILP) for several TSP-D variants that is based on timely synchronizing truck and drone flows; such an MILP is easy to implement but nevertheless leads to competitive results compared with the state-of-the-art MILPs. Furthermore, we introduce dynamic programming recursions to model several TSP-D variants. We show how these dynamic programming recursions can be exploited in an exact branch-and-price approach based on a set partitioning formulation using ng-route relaxation and a three-level hierarchical branching. The proposed branch-and-price can solve instances with up to 39 customers to optimality outperforming the state-of-the-art by more than doubling the manageable instance size. Finally, we analyze different scenarios and show that even a single drone can significantly reduce a route’s completion time when the drone is sufficiently fast.", "keywords": [ "Drone", "Travelling salesman problem", "Computer science", "Truck", "Mathematical optimization", "Integer programming", "Linear programming", "Lagrangian relaxation", "Linear programming relaxation", "Exploit", "Set (abstract data type)", "Last mile (transportation)" ], "cited_by_count": 239, "is_retracted": false, "is_paratext": false, "open_access_url": "https://research.vu.nl/en/publications/0f9ac9eb-c330-4734-90fc-94fdab2e6a46" }, { "id": "https://openalex.org/W3095176261", "doi": "10.1002/cpe.6068", "title": "Solving the last mile problem in logistics: A mobile edge computing and blockchain‐based unmanned aerial vehicle delivery system", "year": 2020, "publication_date": "2020-11-05", "type": "article", "language": "en", "authors": [ "Xuejun Li", "Lina Gong", "Xiao Liu", "Frank Jiang", "Wenyu Shi", "Lingmin Fan", "Han Gao", "Rui Li", "Xu Jia" ], "first_author": "Xuejun Li", "venue": "Concurrency and Computation Practice and Experience", "publisher": "Wiley", "abstract": "Summary The “last mile” problem in logistics is challenging due to its low efficiency and high cost. To address this problem, Unmanned Aerial Vehicle (UAV) delivery such as drone delivery has been proposed and widely accepted as a promising solution. However, currently most of the existing UAV delivery systems are based on Cloud Computing which cannot efficiently meet the requirements of many real‐time services in UAV delivery systems. Meanwhile, the security issues in UAV delivery systems also raise critical concerns due to the existence of multiple participants (such as the sender, middler, and receiver) who may not maintain a mutual trust relationship among them. How to secure the UAV delivery process in such an untrusted environment is still a challenging issue. In this paper, we propose a Mobile Edge Computing (MEC) and blockchain‐based UAV delivery system to resolve the “last mile” problem in logistics. Specifically, based on the MEC architecture, the blockchain nodes are deployed on the edge nodes to facilitate and secure the UAV delivery process. To verify the effectiveness of our proposed solution, a MEC‐based UAV delivery system prototype with a private blockchain on the Ethereum platform is implemented. Through the security analysis and performance evaluation, it is proven that our proposed solution can effectively solve the “last mile” problem and address the security issues in UAV delivery systems.", "keywords": [ "Computer science", "Blockchain", "Drone", "Mobile edge computing", "Edge computing", "Cloud computing", "Enhanced Data Rates for GSM Evolution", "Process (computing)", "Computer security", "Last mile (transportation)", "Distributed computing", "Mile" ], "cited_by_count": 43, "is_retracted": false, "is_paratext": false, "open_access_url": "https://figshare.com/articles/journal_contribution/Solving_the_last_mile_problem_in_logistics_A_mobile_edge_computing_and_blockchain-based_unmanned_aerial_vehicle_delivery_system/20683684" }, { "id": "https://openalex.org/W4380714896", "doi": "10.1007/s10479-023-05418-y", "title": "Collaborative truck multi-drone delivery system considering drone scheduling and en route operations", "year": 2023, "publication_date": "2023-06-15", "type": "article", "language": "en", "authors": [ "Teena Thomas", "Sharan Srinivas", "Chandrasekharan Rajendran" ], "first_author": "Teena Thomas", "venue": "Annals of Operations Research", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Computer science", "Truck", "Scheduling (production processes)", "Heuristic", "Integer programming", "Routing (electronic design automation)", "Cluster analysis", "Job shop scheduling", "Mathematical optimization", "Operations research", "Real-time computing" ], "cited_by_count": 65, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10479-023-05418-y" }, { "id": "https://openalex.org/W4319437469", "doi": "10.1080/16258312.2023.2173488", "title": "Innovative solutions in last mile delivery: concepts, practices, challenges, and future directions", "year": 2023, "publication_date": "2023-02-07", "type": "article", "language": "en", "authors": [ "Wassen A. M. Mohammad", "Yousef Nazih Diab", "Adel Elomri", "Chefi Triki" ], "first_author": "Wassen A. M. Mohammad", "venue": "Supply Chain Forum an International Journal", "publisher": "Taylor & Francis", "abstract": "In the last decade, e-commerce has been growing consistently. Fostered by the covid pandemic, online retail has grown exponentially, particularly in industries including food, clothing, groceries, and many others. This growth in online retailing activities has raised critical logistic challenges, especially in the last leg of the distribution, commonly referred to as the Last Mile. For instance, traditional truck-based home delivery has reached its limit within metropolitan areas and can no longer be an effective delivery method. Driven by technological progress, several other logistic solutions have been deployed as innovative alternatives to deliver parcels. This includes delivery by drones, smart parcel stations, robots, and crowdsourcing, among others. In this setting, this paper aims to provide a comprehensive review and analysis of the latest trends in last-mile delivery solutions from both industry and academic perspectives (see Figure 1 for overview). We use a content analysis literature review to analyse over 80 relevant publications, derive the necessary features of the latest innovation in the last mile delivery, and point out their different maturity levels and the related theoretical and operational challenges.Innovative solutions in last mile delivery: concepts, practices, challenges, and future directionsAll authorsWassen AM Mohammad, Yousef Nazih Diab, Adel Elomri & Chefi Triki https://doi.org/10.1080/16258312.2023.2173488Published online:07 February 2023Figure 1. Overview and Graphical Abstract.Display full sizeFigure 1. Overview and Graphical Abstract.", "keywords": [ "Last mile (transportation)", "Mile", "Metropolitan area", "Food delivery", "Best practice", "Crowdsourcing", "Computer science", "Business", "Marketing", "Geography", "World Wide Web", "Management" ], "cited_by_count": 96, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.tandfonline.com/doi/pdf/10.1080/16258312.2023.2173488?needAccess=true&role=button" }, { "id": "https://openalex.org/W4406342867", "doi": "10.3390/drones9010054", "title": "The Future of Last-Mile Delivery: Lifecycle Environmental and Economic Impacts of Drone-Truck Parallel Systems", "year": 2025, "publication_date": "2025-01-14", "type": "article", "language": "en", "authors": [ "Danwen Bao", "Yu Hong Yan", "Yuhan Li", "Jiajun Chu" ], "first_author": "Danwen Bao", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "With rapid advancements in unmanned aerial vehicle (UAV) technology, its integration into logistics operations has emerged as a promising solution for improving efficiency and sustainability. Among the emerging solutions, a collaborative delivery model involving drones and trucks addresses last-mile delivery challenges by leveraging the complementary strengths of both modes of transport. However, evaluating the environmental and economic impacts of this transportation mode requires a systematic framework to capture its unique characteristics and minimize environmental impacts and costs. This paper investigates the Parallel Drone Scheduling Traveling Salesman Problem (PDSTSP) to evaluate the environmental and economic sustainability of a collaborative drone-truck delivery system. Specifically, a mathematical model for this delivery system is developed to optimize joint delivery operations. Environmental impacts are assessed using a comprehensive Life Cycle Assessment (LCA), including emissions and operational noise, while a Life Cycle Cost Analysis (LCCA) quantifies economic performance across five cost dimensions. Sensitivity analysis explores factors such as delivery density, traffic congestion, and wind conditions. Results show that, compared to the electric vehicle fleet, the proposed model achieves an approximate 20% reduction in carbon emissions, while delivering a 20–30% cost reduction relative to the fuel truck fleet. Drones’ efficiency in short-distance deliveries alleviates trucks’ load, cutting environmental and operational costs. This study offers practical insights and recommendations for implementing drone-truck parallel delivery systems, particularly in high-demand density areas.", "keywords": [ "Drone", "Mile", "Truck", "Last mile (transportation)", "Aeronautics", "Environmental science", "Engineering", "Business", "Aerospace engineering", "Geography" ], "cited_by_count": 44, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/9/1/54/pdf?version=1736851782" }, { "id": "https://openalex.org/W4381616516", "doi": "10.3390/drones7070407", "title": "Development of Heuristic Approaches for Last-Mile Delivery TSP with a Truck and Multiple Drones", "year": 2023, "publication_date": "2023-06-21", "type": "article", "language": "en", "authors": [ "Marco Rinaldi", "Stefano Primatesta", "Martin Bugaj", "Ján Rostáš", "Giorgio Guglieri" ], "first_author": "Marco Rinaldi", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Unmanned Aerial Vehicles (UAVs) are gaining momentum in many civil and military sectors. An example is represented by the logistics sector, where UAVs have been proven to be able to improve the efficiency of the process itself, as their cooperation with trucks can decrease the delivery time and reduce fuel consumption. In this paper, we first state a mathematical formulation of the Travelling Salesman Problem (TSP) applied to logistic routing, where a truck cooperates synchronously with multiple UAVs for parcel delivery. Then, we propose, implement, and compare different sub-optimal routing approaches to the formulated mFSTSP (multiple Flying Sidekick Travelling Salesman Problem) since the inherent combinatorial computational complexity of the problem makes it unattractable for commercial Mixed-Integer Linear Programming (MILP) solvers. A local search algorithm, two hybrid genetic algorithms that permutate feasible and infeasible solutions, and an alternative ad-hoc greedy method are evaluated in terms of the total delivery time of the output schedule. For the sake of the evaluation, the savings in terms of delivery time over the well-documented truck-only TSP solution are investigated for each proposed routing solution, and this is repeated for two different scenarios. Monte Carlo simulations corroborate the results.", "keywords": [ "Travelling salesman problem", "Vehicle routing problem", "Truck", "Mathematical optimization", "Computer science", "Traveling purchaser problem", "Routing (electronic design automation)", "Drone", "Schedule", "Heuristic", "Greedy algorithm", "Integer programming" ], "cited_by_count": 34, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/7/7/407/pdf?version=1687857556" }, { "id": "https://openalex.org/W4376873376", "doi": "10.1080/0960085x.2023.2214744", "title": "Security and privacy risks in drone-based last mile delivery", "year": 2023, "publication_date": "2023-05-17", "type": "article", "language": "en", "authors": [ "Yu-Ju Tu", "Selwyn Piramuthu" ], "first_author": "Yu-Ju Tu", "venue": "European Journal of Information Systems", "publisher": "Palgrave Macmillan", "abstract": "The consideration of drones for last mile delivery brings with it several challenges that include both physical ones such as battery life, drone range, carrying capacity, and form factor of the drone as well as those related to security and privacy of the parties associated with any given packet as well as its content. Privacy and security aspects are significant since last mile delivery drones operate outside the warehouse and are not under complete control of the delivery service operator. This is especially salient with respect to communications between the drone and outside entities that are not necessarily authorised for such communication by the operator. Even if such outside entities are authorised to communicate with the drone, while it is in the open, there may be restrictions on the types of information it can reveal to any given external entity. In addition to an overview of the main security and privacy issues in drone-based last mile delivery, we discuss general security and privacy issues and how these translate to drone-based last mile delivery. We consider various facets of issues related to privacy and security of drone-based last mile delivery. Specifically, we study risks associated with privacy and security in this environment with specific emphasis on those related to codes, external entities, and communication signals. We then identify some of the gaps in associated extant academic literature that could potentially be addressed in future studies.", "keywords": [ "Drone", "Computer security", "Last mile (transportation)", "Computer science", "Internet privacy", "Mile", "Business", "Geography" ], "cited_by_count": 33, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/0960085x.2023.2214744" }, { "id": "https://openalex.org/W4401581373", "doi": "10.3390/vehicles6030066", "title": "Urban Air Mobility for Last-Mile Transportation: A Review", "year": 2024, "publication_date": "2024-08-12", "type": "article", "language": "en", "authors": [ "Nima Moradi", "Wang Chun", "Fereshteh Mafakheri" ], "first_author": "Nima Moradi", "venue": "Vehicles", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Urban air mobility (UAM) is a revolutionary approach to transportation in densely populated cities. UAM involves using small, highly automated aircraft to transport passengers and goods at lower altitudes within urban and suburban areas, aiming to transform how people and parcels move within these environments. On average, UAM can reduce travel times by 30% to 40% for point-to-point journeys, with even greater reductions of 40% to 50% in major cities in the United States and China, compared to land transport. UAM includes advanced airborne transportation options like electric vertical takeoff and landing (eVTOL) aircraft and unmanned aerial vehicles (UAVs or drones). These technologies offer the potential to ease traffic congestion, decrease greenhouse gas emissions, and substantially cut travel times in urban areas. Studying the applications of eVTOLs and UAVs in parcel delivery and passenger transportation poses intricate challenges when examined through the lens of operations research (OR). By OR approaches, we mean mathematical programming, models, and solution methods addressing eVTOL- and UAV-aided parcel/people transportation problems. Despite the academic and practical importance, there is no review paper on eVTOL- and UAV-based optimization problems in the UAM sector. The present paper, applying a systematic literature review, develops a classification scheme for these problems, dividing them into routing and scheduling of eVTOLs and UAVs, infrastructure planning, safety and security, and the trade-off between efficiency and sustainability. The OR methodologies and the characteristics of the solution methods proposed for each problem are discussed. Finally, the study gaps and future research directions are presented alongside the concluding remarks.", "keywords": [ "Mile", "Transport engineering", "Aeronautics", "Engineering", "Geography" ], "cited_by_count": 57, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.3390/vehicles6030066" }, { "id": "https://openalex.org/W3121017033", "doi": "10.1016/j.trb.2020.11.011", "title": "A branch-and-cut algorithm for the vehicle routing problem with drones", "year": 2021, "publication_date": "2021-01-13", "type": "article", "language": "en", "authors": [ "Felix Tamke", "Udo Buscher" ], "first_author": "Felix Tamke", "venue": "Transportation Research Part B Methodological", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Routing (electronic design automation)", "Mathematical optimization", "Branch and cut", "Linear programming", "Range (aeronautics)", "Flexibility (engineering)", "Integer programming", "Vehicle routing problem", "Lagrangian relaxation", "Linear programming relaxation" ], "cited_by_count": 200, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trb.2020.11.011" }, { "id": "https://openalex.org/W3041611419", "doi": "10.1016/j.trb.2020.06.011", "title": "Drone routing with energy function: Formulation and exact algorithm", "year": 2020, "publication_date": "2020-07-11", "type": "article", "language": "en", "authors": [ "Chun Cheng", "Yossiri Adulyasak", "Louis-Martin Rousseau" ], "first_author": "Chun Cheng", "venue": "Transportation Research Part B Methodological", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Mathematical optimization", "Energy consumption", "Computer science", "Drone", "Routing (electronic design automation)", "Subgradient method", "Nonlinear system", "Benchmark (surveying)", "Energy (signal processing)", "Mathematics", "Engineering" ], "cited_by_count": 232, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trb.2020.06.011" }, { "id": "https://openalex.org/W4385064242", "doi": "10.1038/s41598-023-38922-z", "title": "Critical assessment of emissions, costs, and time for last-mile goods delivery by drones versus trucks", "year": 2023, "publication_date": "2023-07-21", "type": "article", "language": "en", "authors": [ "Aishwarya Raghunatha", "Emma Lindkvist", "Patrik Thollander", "Erika Hansson", "Greta Jonsson" ], "first_author": "Aishwarya Raghunatha", "venue": "Scientific Reports", "publisher": "Nature Portfolio", "abstract": "Electric drones as an autonomous mode of transport are scaling up to transform last-mile goods delivery, raising an urgent need for assessing impacts of drone transport from a systems perspective. In this paper, we conduct systems analyses to assess the environmental, economic, and delivery time impact of large drones for delivery scenarios to pick-up centers between mid-size cities predominantly in rural areas, and deliveries within city limits compared with electric and diesel trucks. Results show that large drones have lower emissions than diesel trucks for deliveries in rural areas and that drones don't compete with electric trucks, mainly due to the high energy demand required for take-off and landing for each delivery. Furthermore, we show that electric drones are an economically more cost-effective option than road-bound transport modes such as diesel and electric trucks due to the high degree of automation, and also provide the fastest delivery times. Our analysis provides unique insights that drones can address rapid electrification and emergency applications due to low costs, high flexibility, and fast operations. However, for regulators and practitioners to realize it as an emission-friendly option it is necessary to determine the optimal size of drones, particularly for use cases in urban areas, avoid very low landings for deliveries, and have home deliveries instead of pick-up points.", "keywords": [ "Truck", "Mile", "Drone", "Transport engineering", "Computer science", "Aeronautics", "Business", "Environmental science", "Engineering", "Automotive engineering", "Geography", "Biology" ], "cited_by_count": 47, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.nature.com/articles/s41598-023-38922-z.pdf" }, { "id": "https://openalex.org/W3011794261", "doi": "10.1016/j.trc.2020.02.030", "title": "Truck-drone team logistics: A heuristic approach to multi-drop route planning", "year": 2020, "publication_date": "2020-03-13", "type": "article", "language": "en", "authors": [ "Pedro Luis González Rodríguez", "David Canca", "José Luis Andrade-Pineda", "Marcos Calle Suárez", "Jose Miguel Leon-Blanco" ], "first_author": "Pedro Luis González Rodríguez", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Vehicle routing problem", "Routing (electronic design automation)", "Simulated annealing", "Truck", "Heuristic", "Operations research", "Mathematical optimization", "Engineering", "Artificial intelligence", "Algorithm" ], "cited_by_count": 247, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/11441/167149" }, { "id": "https://openalex.org/W3006984451", "doi": "10.1016/j.promfg.2020.01.338", "title": "Vehicle Routing Problem with Drones for Last Mile Delivery", "year": 2019, "publication_date": "2019-01-01", "type": "article", "language": "en", "authors": [ "Patchara Kitjacharoenchai", "Seokcheon Lee" ], "first_author": "Patchara Kitjacharoenchai", "venue": "Procedia Manufacturing", "publisher": "Elsevier BV", "abstract": "E-commerce and retail companies are seeking ways to cut delivery times and costs by exploring opportunities to use drones for making last mile delivery deliveries. In recent years, drone routing and scheduling has become a highly active area of research. This research addresses the delivery concept of a truck-drone combination along with the idea of allowing autonomous drones to fly from delivery trucks, make deliveries, and fly to delivery trucks nearby. The proposed model considers the synchronized truck drone routing model by allowing multiple drones to fly from a truck, serve customers and immediately return to the same truck for the battery swap and package retrieval. The model also takes into account both trucks and drones capacities to ensure that the amount of loads carried by each drone must not exceed its capacity and the total amount of loads in each delivery route must be less than truck’s capacity. The goal is to find the optimal routes of both trucks and drones which minimize the total arrival time of both trucks and drones at the depot after completing the deliveries. The problem can be solved by the formulated mixed integer programming (MIP) for the small size problem. Numerical results in the case study and benchmark problems are presented to show the delivery time improvement over the delivery time from other delivery types.", "keywords": [ "Drone", "Truck", "Routing (electronic design automation)", "Swap (finance)", "Computer science", "Scheduling (production processes)", "Integer programming", "Vehicle routing problem", "Transport engineering", "Mile", "Last mile (transportation)", "Operations research" ], "cited_by_count": 28, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2351978920304054/pdf" }, { "id": "https://openalex.org/W2991069856", "doi": "10.1016/j.trpro.2019.09.017", "title": "Drones for last mile logistics: Baloney or part of the solution?", "year": 2019, "publication_date": "2019-01-01", "type": "article", "language": "en", "authors": [ "Stephan S. W. Müller", "Christian Rudolph", "Christian Jänke" ], "first_author": "Stephan S. W. Müller", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "Road-based mobility is increasingly under pressure, with remarkable dynamics in the last decade in terms of \\npollution, congestion, speed delivery expectation etc. Such pressures point to a limitation of the efficiency of roadbased mobility for further economic and social development. A mainstream solution is considered by electrified, \\nautomated mobility-services based on the road transport. This article discusses an alternative future pathway based \\non an evolutionary economic perspective. The case study employed concerns “drones for last-mile logistics”. The \\nanalysis makes clear that current efforts to enhance efficiency by electrifying and automating the established vehicle \\ntechnology are short-term solutions. The main concern in the article is to broaden the policy-supported search for \\nfuture mobility solution. The disruption of efficiency limitations is the key to sustainable social and economic \\ndevelopment.", "keywords": [ "Drone", "Mile", "Aeronautics", "Last mile (transportation)", "Transport engineering", "Engineering", "Business", "Computer security", "Computer science", "Geography" ], "cited_by_count": 28, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2352146519304284/pdf" }, { "id": "https://openalex.org/W4200257181", "doi": "10.3390/su14010360", "title": "A Literature Review of Drone-Based Package Delivery Logistics Systems and Their Implementation Feasibility", "year": 2021, "publication_date": "2021-12-29", "type": "article", "language": "en", "authors": [ "Taha Benarbia", "Kyandoghere Kyamakya" ], "first_author": "Taha Benarbia", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "In recent years, e-commerce businesses have seen an increase in the daily volume of packages to be delivered, as well as an increase in the number of particularly demanding customer expectations. In this respect, the delivery mechanism became prohibitively expensive, particularly for the final kilometer. To stay competitive and meet the increased demand, businesses began to look for innovative autonomous delivery options for the last mile, such as autonomous unmanned aerial vehicles/drones, which are a promising alternative for the logistics industry. Following the success of drones in surveillance and remote sensing, drone delivery systems have begun to emerge as a new solution to reduce delivery costs and delivery time. In the coming years, autonomous drone sharing systems will be an unavoidable logistical solution, especially with the new laws/recommendations introduced by the Flight World Organization on how to organize the operations of these special unmanned airline systems. This paper provides a comprehensive literature survey on a set of relevant research issues and highlights the representative solutions and concepts that have been proposed thus far in the design and modeling of the logistics of drone delivery systems, with the purpose of discussing the respective performance levels reached by the various suggested approaches. Furthermore, the paper also investigates the central problems to be addressed and briefly discusses and outlines a series of interesting new research avenues of relevance for drone-based package delivery systems.", "keywords": [ "Drone", "Last mile (transportation)", "Computer science", "Relevance (law)", "Delivery Performance", "Systems engineering", "Operations research", "Business", "Engineering", "Process management", "Mile" ], "cited_by_count": 227, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/14/1/360/pdf?version=1640845639" }, { "id": "https://openalex.org/W2999032258", "doi": "10.1287/trsc.2019.0928", "title": "Strategic Network Design for Parcel Delivery with Drones Under Competition", "year": 2020, "publication_date": "2020-01-01", "type": "article", "language": "en", "authors": [ "Gohram Baloch", "Fatma Gzara" ], "first_author": "Gohram Baloch", "venue": "Transportation Science", "publisher": "Institute for Operations Research and the Management Sciences", "abstract": "This paper studies the economic desirability of unmanned aerial vehicle (UAV) parcel delivery and its effect on e-retailer distribution networks while taking into account technological limitations, government regulations, and customer behavior. We consider an e-retailer offering multiple same-day delivery services including a fast UAV service and develop a distribution network design formulation under service-based competition where the services offered by the e-retailer not only compete with the stores (convenience, grocery, etc.) but also with each other. Competition is incorporated using the multinomial logit market share model. To solve the resulting nonlinear mathematical formulation, we develop a novel logic-based Benders decomposition approach. We build a case based on New York City, carry out extensive numerical testing, and perform sensitivity analyses over delivery charge, delivery time, government regulations, technological limitations, customer behavior, and market size. The results show that government regulations, technological limitations, and service charge decisions each play a vital role in the future of UAV delivery.", "keywords": [ "Competition (biology)", "Drone", "Service (business)", "Government (linguistics)", "Multinomial logistic regression", "Service delivery framework", "Business", "Operations research", "Computer science", "Industrial organization", "Marketing", "Engineering" ], "cited_by_count": 63, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1287/trsc.2019.0928" }, { "id": "https://openalex.org/W4387331274", "doi": "10.1002/net.22190", "title": "Last‐mile delivery with drone and lockers", "year": 2023, "publication_date": "2023-10-04", "type": "article", "language": "en", "authors": [ "Marco Antonio Boschetti", "Stefano Novellani" ], "first_author": "Marco Antonio Boschetti", "venue": "Networks", "publisher": "Wiley", "abstract": "Abstract In this article, we define a new routing problem that arises in the last‐mile delivery of parcels, in which customers can be served either directly at home by a capacitated truck, or possibly with a drone carried on the truck, or in a self‐service mode using one of the available lockers. We investigate four different formulations, and for one of them, we propose a branch‐and‐cut approach. We also discuss some possible variants of the original problem. In the computational experiments, we analyze and compare the performance of the four formulations for the problem and its variants, and we provide some useful managerial insights.", "keywords": [ "Drone", "Truck", "Computer science", "Last mile (transportation)", "Vehicle routing problem", "Routing (electronic design automation)", "Service (business)", "Operations research", "Mile", "Computer network", "Mathematics", "Business" ], "cited_by_count": 21, "is_retracted": false, "is_paratext": false, "open_access_url": "https://cris.unibo.it/bitstream/11585/945394/4/TSP_with_Drone_and_Lockers_Final_nonetwroks.pdf" }, { "id": "https://openalex.org/W4292262934", "doi": "10.3390/asi5040082", "title": "Toward a Modern Last-Mile Delivery: Consequences and Obstacles of Intelligent Technology", "year": 2022, "publication_date": "2022-08-17", "type": "article", "language": "en", "authors": [ "Shahryar Sorooshian", "Shila Khademi Sharifabad", "Mehrdad Parsaee", "Ali Reza Afshari" ], "first_author": "Shahryar Sorooshian", "venue": "Applied System Innovation", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Last-mile delivery (LMD) is essential in supply chains, and providers of logistics services are aware that they must adapt to changing customer and society expectations, competition challenges, and modern technologies. In light of the importance of artificial intelligence (AI) in modern technologies, this article employed a narrative literature review to recognize impacts of AI-powered technologies that aid in optimizing the LMD component. For this study, two possible classes of technologies were considered: tangible technologies, such as robots, drones, and autonomous vehicles, and intangible technologies, such as decision support tools and operating systems. Thus, this article frames potential developments in modern LMD, taking into account the fact that technological advancement brings both opportunities and challenges. According to this literature review, the modern version of LMD is capable of providing services that are both more productive and more sustainable, thus satisfying demands for better services. Last but not least, another goal of this article was to look into the challenges that limit the benefits of modern LMDs. Finally, suggestions are provided as a resource for practitioners and policymakers working in the supply chain to improve performance.", "keywords": [ "Emerging technologies", "Supply chain", "Drone", "Computer science", "Last mile (transportation)", "Business", "Engineering management", "Risk analysis (engineering)", "Knowledge management", "Marketing", "Mile", "Engineering" ], "cited_by_count": 76, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2571-5577/5/4/82/pdf?version=1660719192" }, { "id": "https://openalex.org/W3176508160", "doi": "10.1109/access.2021.3092039", "title": "6G Enabled Unmanned Aerial Vehicle Traffic Management: A Perspective", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Rakesh Shrestha", "Rojeena Bajracharya", "Shiho Kim" ], "first_author": "Rakesh Shrestha", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Unmanned aerial vehicles (UAVs) and UAV traffic management (UTM) have drawn attention for applications such as parcel delivery, aerial mapping, agriculture, and surveillance based on line-of-sight (LoS) links. UTM is essential to operate multiple fully autonomous UAVs safely beyond the visual line of sight (BVLoS) in the future dense UAV traffic environment. Various research and development teams globally take UTM initiatives and work on platform testing with different industrial partners. In the future, urban airspace will be congested with various types of autonomous aerial vehicles, thereby resulting in complex air-traffic management caused by communication issues. The UTM requires an efficient communication backbone to handle all airborne communication services. Existing cellular networks are suitable only for terrestrial communication and have limitations in supporting aerial communications. These issues motivate the investigation of an appropriate communication technology for advanced UTM systems. Thus, in this study, we present a future perspective of 6G-enabled UTM ecosystems in a very dense and urban air-traffic scenario focusing on non-terrestrial features, including aerial and satellite communication. We also introduce several urban airspace segmentation and discuss a strategic management framework for dynamic airspace traffic management and conflict-free UAV operations. The UTM enhances the adaptive use of the airspace by shaping the airspace with the overall aim of maximizing the capability and efficiency of the network. We also discuss the 6G multi-layer parameters i.e., space, air, and terrestrial, for safe and efficient urban air transportation in three-dimensional space. Moreover, we discuss the issues and challenges faced by future UTM systems and provide tentative solutions. We subsequently extend the vision of the UTM system and design an advanced and fully autonomous 6G-based UTM system.", "keywords": [ "Computer science", "Air traffic management", "Air traffic control", "Perspective (graphical)", "Systems engineering", "Engineering", "Artificial intelligence", "Aerospace engineering" ], "cited_by_count": 147, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/access.2021.3092039" }, { "id": "https://openalex.org/W4387613703", "doi": "10.1016/j.eswa.2023.122149", "title": "Parcel consolidation approach and routing algorithm for last-mile delivery by unmanned aerial vehicles", "year": 2023, "publication_date": "2023-10-13", "type": "article", "language": "en", "authors": [ "Xiaohui Li", "Pengyu Yan", "Kaize Yu", "Peifan Li", "Yuchen Liu" ], "first_author": "Xiaohui Li", "venue": "Expert Systems with Applications", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Computer science", "Last mile (transportation)", "Consolidation (business)", "Vehicle routing problem", "Real-time computing", "Operations research", "Mathematical optimization", "Routing (electronic design automation)", "Mile", "Computer network", "Engineering" ], "cited_by_count": 29, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.eswa.2023.122149" }, { "id": "https://openalex.org/W4289755354", "doi": "10.1016/j.eswa.2022.118351", "title": "Improving the efficiency of last-mile delivery with the flexible drones traveling salesman problem", "year": 2022, "publication_date": "2022-08-04", "type": "article", "language": "en", "authors": [ "Shih‐Hao Lu", "R.J. Kuo", "Yi-Ting Ho", "Anh-Tu Nguyen" ], "first_author": "Shih‐Hao Lu", "venue": "Expert Systems with Applications", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Computer science", "Truck", "Last mile (transportation)", "Heuristic", "Real-time computing", "Operations research", "Mile", "Engineering", "Artificial intelligence", "Automotive engineering" ], "cited_by_count": 33, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.eswa.2022.118351" }, { "id": "https://openalex.org/W3161165561", "doi": "10.1016/j.trc.2021.103172", "title": "The Multi-visit Traveling Salesman Problem with Multi-Drones", "year": 2021, "publication_date": "2021-05-19", "type": "article", "language": "en", "authors": [ "Zhihao Luo", "Mark Poon", "Zhenzhen Zhang", "Zhong Liu", "Andrew E. B. Lim" ], "first_author": "Zhihao Luo", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Payload (computing)", "Computer science", "Mathematical optimization", "Network packet", "Mathematics", "Algorithm", "Computer network" ], "cited_by_count": 190, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2021.103172" }, { "id": "https://openalex.org/W4306632378", "doi": "10.1016/j.ejor.2022.10.015", "title": "Drone location and vehicle fleet planning with trucks and aerial drones", "year": 2022, "publication_date": "2022-10-17", "type": "article", "language": "en", "authors": [ "Alexander Rave", "Pirmin Fontaine", "Heinrich C. Kuhn" ], "first_author": "Alexander Rave", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Payload (computing)", "Context (archaeology)", "Transport engineering", "Computer science", "Operations research", "Engineering", "Computer security", "Geography", "Network packet", "Automotive engineering" ], "cited_by_count": 112, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ejor.2022.10.015" }, { "id": "https://openalex.org/W4389469358", "doi": "10.1016/j.trc.2023.104448", "title": "A cyber-physical social system for autonomous drone trajectory planning in last-mile superchilling delivery", "year": 2023, "publication_date": "2023-12-07", "type": "article", "language": "en", "authors": [ "Haishi Liu", "Yung Po Tsang", "C.K.M. Lee" ], "first_author": "Haishi Liu", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Heuristic", "Computer science", "Last mile (transportation)", "Trajectory", "Operations research", "Mile", "Transport engineering", "Simulation", "Engineering", "Artificial intelligence" ], "cited_by_count": 36, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2023.104448" }, { "id": "https://openalex.org/W3193445169", "doi": "10.1108/jm2-09-2020-0241", "title": "Assessing the sustainability of using drone technology for last-mile delivery in a blood supply chain", "year": 2021, "publication_date": "2021-08-16", "type": "article", "language": "en", "authors": [ "Ehsan Rashidzadeh", "Seyyed Mohammad Hadji Molana", "Roya Soltani", "Ashkan Hafezalkotob" ], "first_author": "Ehsan Rashidzadeh", "venue": "Journal of Modelling in Management", "publisher": "Emerald Publishing Limited", "abstract": "Purpose Delivery management of perishable products such as blood in a supply chain is a considerable issue such that the last-mile delivery, which refers to deliver goods to the end user as fast as possible takes into account as one of the most important, expensive and, polluting segments in the entire supply chain. Regardless of economic challenges, the last-mile delivery faces social and environmental barriers to continuing operations while complying with environmental and social standards, therefore incorporating sustainability into last-mile logistic strategy is no longer an option but rather a necessity. Accordingly, the purpose of this paper is to consider a last-mile delivery in a blood supply chain in terms of using appropriate technologies such as drones to assess sustainability. Design/methodology/approach The authors discuss the impact of drone technology on last-mile delivery and its importance in achieving sustainability. They focus on the effect of using drones on CO2 emission, costs and social benefits by proposing a multi-objective mathematical model to assess sustainability in the last-mile delivery. A preemptive fuzzy goal programming approach to solve the model and measure the achievement degree of sustainability is conducted by using a numerical example to show the capability and usefulness of the suggested model, solution approach and, impact of drone technology in achieving all three aspects of sustainability. Findings The findings illustrate the achievement degree of sustainability in the delivery of blood based on locating distribution centers and allocating drones. Moreover, a comparison between drones and conventional vehicles is carried out to show the preference of using drones in reaching sustainability. A sensitivity analysis on aspects of sustainability and specifications of drone technology is conducted for validating the obtained results and distinguishing the most dominant aspect and parameters in enhancing the achievement degree of sustainability. Originality/value To the best of the authors’ knowledge, no research has considered the assessment of sustainability in the last-mile delivery of blood supply chain with a focus on drone technology.", "keywords": [ "Last mile (transportation)", "Sustainability", "Drone", "Supply chain", "Mile", "Business", "Environmental economics", "Supply chain management", "Computer science", "Operations management", "Marketing", "Engineering" ], "cited_by_count": 37, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1108/jm2-09-2020-0241" }, { "id": "https://openalex.org/W2994913150", "doi": "10.1016/j.trd.2019.11.024", "title": "Effects of a hovering Unmanned Aerial Vehicle on urban soundscapes perception", "year": 2020, "publication_date": "2020-01-01", "type": "article", "language": "en", "authors": [ "Antonio J. Torija", "Zhengguang Li", "Rod Self" ], "first_author": "Antonio J. Torija", "venue": "ePrints Soton (University of Southampton)", "publisher": "University of Southampton", "abstract": null, "keywords": [ "Drone", "Annoyance", "Soundscape", "Noise (video)", "Noise pollution", "Loudness", "Noise control", "Aeronautics", "Traffic noise", "Transport engineering", "Computer science", "Engineering" ], "cited_by_count": 116, "is_retracted": false, "is_paratext": false, "open_access_url": "http://usir.salford.ac.uk/id/eprint/53180/1/Torija_et_al_TRD_2019_AcceptedVersion.pdf" }, { "id": "https://openalex.org/W3037300836", "doi": "10.1007/s10846-020-01223-y", "title": "A New Parcel Delivery System with Drones and a Public Train", "year": 2020, "publication_date": "2020-06-25", "type": "article", "language": "en", "authors": [ "Hailong Huang", "Andrey V. Savkin", "Chao Huang" ], "first_author": "Hailong Huang", "venue": "Journal of Intelligent & Robotic Systems", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Aeronautics", "Computer science", "Delivery system", "Transport engineering", "Engineering", "Biology", "Biomedical engineering" ], "cited_by_count": 61, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/s10846-020-01223-y" }, { "id": "https://openalex.org/W2268183161", "doi": "10.1260/1756-8293.7.4.395", "title": "Design and Control of an Unmanned Aerial Vehicle for Autonomous Parcel Delivery with Transition from Vertical Take-off to Forward Flight – VertiKUL, a Quadcopter Tailsitter", "year": 2015, "publication_date": "2015-12-01", "type": "article", "language": "en", "authors": [ "Menno Hochstenbach", "Cyriel Notteboom", "Bart Theys", "Joris De Schutter" ], "first_author": "Menno Hochstenbach", "venue": "International Journal of Micro Air Vehicles", "publisher": "SAGE Publishing", "abstract": "This paper presents the design and control of VertiKUL, a Vertical Take-Off and Landing (VTOL) transitioning tailsitter Unmanned Aerial Vehicle (UAV), capable of hover flight and forward flight for the application of parcel delivery. In contrast to existing transitioning UAVs, VertiKUL is not controlled by control surfaces, but exclusively by four propellers using differential thrust during hover flight, transition and forward flight. A numerical design method optimising range and payload is developed for initial sizing. A simulation model is implemented in Simulink to evaluate different control strategies before conducting test flights. A unique mid-level control strategy enabling intuitive control of VertiKUL which requires no pilot skills is developed. Fluent transition from hover to forward flight is achieved through an autonomous control strategy. Attitude control based on quaternions instead of Euler-angles is implemented to avoid singularities. The resulting design, VertiKUL, is built and test flown.", "keywords": [ "Quadcopter", "Payload (computing)", "Thrust", "Flight test", "Aerodynamics", "Aerospace engineering", "Simulation", "Range (aeronautics)", "Attitude control", "Thrust vectoring", "Flight control surfaces", "Computer science" ], "cited_by_count": 106, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1260/1756-8293.7.4.395" }, { "id": "https://openalex.org/W2756240103", "doi": "10.1109/tase.2022.3175565", "title": "Autonomous Recharging and Flight Mission Planning for Battery-Operated Autonomous Drones", "year": 2022, "publication_date": "2022-05-19", "type": "article", "language": "en", "authors": [ "Rashid Alyassi", "Majid Khonji", "Areg Karapetyan", "Chi-Kin Chau", "Khaled Elbassioni", "Chien-Ming Tseng" ], "first_author": "Rashid Alyassi", "venue": "IEEE Transactions on Automation Science and Engineering", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Unmanned aerial vehicles (UAVs), commonly known as drones, are being increasingly deployed throughout the globe as a means to streamline monitoring, inspection, mapping, and logistic routines. When dispatched on autonomous missions, drones require an intelligent decision-making system for trajectory planning and tour optimization. Given the limited capacity of their onboard batteries, a key design challenge is to ensure the underlying algorithms can efficiently optimize the mission objectives along with recharging operations during long-haul flights. With this in view, the present work undertakes a comprehensive study on automated tour management systems for an energy-constrained drone: (1) We construct a machine learning model that estimates the energy expenditure of typical multi-rotor drones while accounting for real-world aspects and extrinsic meteorological factors. (2) Leveraging this model, the joint program of flight mission planning and recharging optimization is formulated as a multi-criteria Asymmetric Traveling Salesman Problem (ATSP), wherein a drone seeks for the time-optimal energy-feasible tour that visits all the target sites and refuels whenever necessary. (3) We devise an efficient approximation algorithm with provable worst-case performance guarantees and implement it in a drone management system, which supports real-time flight path tracking and re- computation in dynamic environments. (4) The effectiveness and practicality of the proposed approach are validated through extensive numerical simulations as well as real-world experiments. Note to Practitioners—This study is stimulated by the need for developing pragmatic and provably efficient automated tour management systems for UAVs deployed on energy-constrained, long-distance flight missions. As such, UAVs provide a nifty platform for facilitating environmental monitoring, disaster management, transport of medical supplies, as well as expediting last-mile deliveries. However, existing path planners generally fall short of capturing several crucial aspects, such as detailed power consumption model (e.g., factoring in payload, wind speed and direction) or performance guarantees, potentially leading to underutilized or infeasible routing decisions. To address these issues, the present work proposes a theoretically-backed routing approach with a certifiable degree of optimality and develops an effective, practical power consumption evaluation model for multi-rotor UAVs, verified on multiple drone models.", "keywords": [ "Drone", "Aeronautics", "Motion planning", "Battery (electricity)", "Engineering", "Computer science", "Robot", "Systems engineering", "Aerospace engineering", "Control engineering", "Automotive engineering", "Artificial intelligence" ], "cited_by_count": 211, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/8856/10094220/09779119.pdf" }, { "id": "https://openalex.org/W4388128130", "doi": "10.1049/itr2.12437", "title": "CO 2 emissions and delivery time of last‐mile drone delivery using trucks", "year": 2023, "publication_date": "2023-11-01", "type": "article", "language": "en", "authors": [ "Sung Ho Hur", "Minsu Won" ], "first_author": "Sung Ho Hur", "venue": "IET Intelligent Transport Systems", "publisher": "Institution of Engineering and Technology", "abstract": "Abstract The shift in consumer behaviour from in‐person to online shopping has led to an increase in parcel delivery volume and its associated negative impacts, such as CO 2 emissions in cities. With the emergence of drone‐delivery technologies, the authors analyzed a joint delivery method using drones and trucks, which is an emerging alternative solution for last‐mile delivery in terms of CO 2 emissions and delivery time. The analysis verified the highest possible level of reduction in CO 2 emissions for the simultaneous and strategic operation of drones and trucks compared to diesel‐ or electric‐only truck operations. Moreover, this approach leads to reduced delivery times. A sensitivity analysis was performed to optimize the delivery‐drone flight performance in a drone‐and‐truck delivery strategy. It was found that a 1.5‐km drone flight performance was sufficient when considering the reasonable assumptions adopted in this study. Furthermore, based on the analysis results, drone‐and‐truck cooperative delivery strategies may not provide a significant advantage in terms of CO 2 emissions compared with alternative transportation modes, such as fuel‐cell trucks with sufficiently low emissions. It has been empirically verified that changes in CO 2 emissions are proportional to the number of clusters. However, there is a risk of local optima due to microscopic fluctuations among neighbouring cluster numbers, which occurs during the search for the optimal number of clusters.", "keywords": [ "Drone", "Truck", "Diesel fuel", "Food delivery", "Transport engineering", "Last mile (transportation)", "Cluster (spacecraft)", "Mile", "Automotive engineering", "Environmental science", "Computer science", "Engineering" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/itr2.12437" }, { "id": "https://openalex.org/W4395475010", "doi": "10.1016/j.trc.2024.104615", "title": "Sustainable last-mile distribution with autonomous delivery robots and public transportation", "year": 2024, "publication_date": "2024-04-25", "type": "article", "language": "en", "authors": [ "Annarita De Maio", "Gianpaolo Ghiani", "Demetrio Laganà", "Emanuele Manni" ], "first_author": "Annarita De Maio", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": "In recent years, the rapid growth of e-commerce and the need to make last-mile logistics more sustainable have stimulated the development of new distribution paradigms, based on air drones and autonomous delivery robots, which are less sensitive to traffic congestion. In this article we deal with a routing problem in which a fleet of autonomous delivery robots can travel not only on the road network but also on the public transportation system (or part of it) to extend their range of action with a given battery capacity. The problem entails building delivery robot routes synchronized with the rides of the public transportation lines, enabling robots to drop on/off public vehicles, where they use dedicated compartments, to reach customers that would be otherwise out of reach. To this purpose, we develop a tailored destroy-and-repair mechanism that, embedded into a neighborhood search algorithm, allows to effectively explore the feasibility region of large-scale instances. Extensive computational results on instances resembling the distribution of drugs to pharmacies in Rome (Italy) show that the proposed algorithmic mechanism allows to obtain a cost reduction up to about 7.5% with respect to a more traditional approach. Moreover, from a managerial point of view, our experiments show that autonomous delivery robots combined with public transportation can provide huge benefits in terms of costs and emissions reduction, when compared to both traditional and electric vans.", "keywords": [ "Mile", "Last mile (transportation)", "Public transport", "Business", "Transport engineering", "Robot", "Distribution (mathematics)", "Computer science", "Engineering", "Geography", "Artificial intelligence" ], "cited_by_count": 67, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2024.104615" }, { "id": "https://openalex.org/W4313413234", "doi": "10.1109/tase.2022.3232025", "title": "Review of Navigation Methods for UAV-Based Parcel Delivery", "year": 2023, "publication_date": "2023-01-02", "type": "article", "language": "en", "authors": [ "Didula Dissanayaka", "Thumeera R. Wanasinghe", "Oscar De Silva", "Awantha Jayasiri", "George K. I. Mann" ], "first_author": "Didula Dissanayaka", "venue": "IEEE Transactions on Automation Science and Engineering", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "This paper presents a comprehensive review of state-of-the-art navigation methods available for unmanned aerial vehicles (UAVs) used in parcel delivery. Particularly, the paper focuses on state-of-the-art sensor configurations, multi-sensor data fusion architectures, and their performance when employed for UAV navigation. Additionally, this paper presents the associated safety regulations for UAV navigation currently imposed by regulatory bodies in US and Canada. The existing navigation solutions sometimes produce degenerative results due to GPS loss, multipath signals, spoofing events, and other sensor degradation scenarios. Therefore, this article investigates the suitability of integrating visual lidar odometry and mapping (VLOAM) with GPS to overcome the limitations of existing navigation solutions. A comparative study of the multi-sensory combined solutions is presented with numerical simulations, validating the regulatory compliance of VLOAM and GPS integrated system under common GPS failure cases. Note to Practitioners—This work was motivated by the need for a survey on existing UAV navigation methods for parcel delivery applications. Different UAV navigation methods exist, depending on the sensors used and the sensor fusion architectures, with varying degrees of localization accuracy. It can be challenging for researchers and practitioners to decide which method to adopt for their application while complying with the existing safety regulations. Therefore, this paper presents an overview of the current safety regulation for UAV navigation and evaluates the state-of-the-art navigation methods against regulatory safety compliance. Additionally, a numerically validated safe navigation method is suggested for UAV-based parcel delivery. This paper provides researchers and practitioners with comprehensive reference sources in the UAV navigation field, which can help them develop suitable solutions to ensure safe navigation.", "keywords": [ "Computer science", "Environmental science", "Marine engineering", "Remote sensing", "Engineering", "Real-time computing", "Simulation", "Geology" ], "cited_by_count": 105, "is_retracted": false, "is_paratext": false, "open_access_url": "https://nrc-publications.canada.ca/eng/view/accepted/?id=0df92bfe-cdff-4396-af67-b4eb226210bb" }, { "id": "https://openalex.org/W3015416080", "doi": "10.1093/jcde/qwaa033", "title": "Last mile delivery drone selection and evaluation using the interval-valued inferential fuzzy TOPSIS", "year": 2020, "publication_date": "2020-02-03", "type": "article", "language": "en", "authors": [ "Farjana Nur", "Ayat Alrahahleh", "Reuben F. V. Burch", "Kari L. Babski-Reeves", "Mohammad Marufuzzaman" ], "first_author": "Farjana Nur", "venue": "Journal of Computational Design and Engineering", "publisher": "Oxford University Press", "abstract": "Abstract The last mile delivery option has become a focal point of academic research and industrial development in recent years. Multiple factors such as increased demands on delivery flexibility, customer requirements, delivery urgency, and many others are enforcing to adopt this option. For fulfilling this paradigm shift in delivery and providing additional flexibility, drones can be considered as a viable option to use for last mile delivery cases. Numerous drones are available in the market with varying capacities and functionalities, posing a significant challenge for decision-makers to select the most appropriate drone type for a specific application. In this purpose, this study proposes a comprehensive list of criterions that can be used to compare a set of available last mile delivery drones. Additionally, we introduced a systematic multi-criterion, multi-personnel decision making approach, referred to as interval-valued inferential fuzzy TOPSIS method. This method is robust and can handle the fuzziness in decision making, thereby providing quality drone selection decisions under different applications. We then apply this method to a real-life test setting. Results suggest that smaller drones or quadcopters are considered viable to use in urban environments while long-range drones are preferred for the last mile delivery needs in rural settings.", "keywords": [ "Drone", "Last mile (transportation)", "TOPSIS", "Flexibility (engineering)", "Mile", "Computer science", "Operations research", "Risk analysis (engineering)", "Engineering", "Mathematics", "Business", "Geography" ], "cited_by_count": 37, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1093/jcde/qwaa033" }, { "id": "https://openalex.org/W2883647941", "doi": "10.1109/lra.2018.2856282", "title": "Last-Centimeter Personal Drone Delivery: Field Deployment and User Interaction", "year": 2018, "publication_date": "2018-07-16", "type": "article", "language": "en", "authors": [ "Przemyslaw Kornatowski", "Anand Bhaskaran", "Grégoire Heitz", "Stefano Mintchev", "Dario Floreano" ], "first_author": "Przemyslaw Kornatowski", "venue": "IEEE Robotics and Automation Letters", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Drones are rapidly becoming an affordable and often faster solution for parcel delivery than terrestrial vehicles. Existing transportation drones and software infrastructures are mostly designed by logistics companies for trained users and dedicated infrastructure, and are to be used for either long range (<;150 km) or last-mile delivery (<;20 km). This letter presents Dronistics, an integrated software and hardware system for last-centimeter (<;5 km) person-to-person delivery using cargo drones. The system is conceived to be intuitive and intrinsically safe to enable short-distance deliveries between inexperienced users. Dronistics is composed of a safe foldable drone (PackDrone) and a web application software to intuitively control and track the drone in real time. In order to assess Dronistics' user acceptance, we conducted 150 deliveries over one month on the EPFL campus in Switzerland. Here we describe the results of these tests by analyzing flight statistics, environmental conditions, and user reactions. Moreover, we also describe technical problems that occurred during flight tests and solutions that could prevent them.", "keywords": [ "Drone", "Software deployment", "Software", "Computer science", "Last mile (transportation)", "Mile", "Aeronautics", "Computer security", "Engineering", "Software engineering", "Operating system", "Geography" ], "cited_by_count": 61, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/7083369/8386768/08411102.pdf" }, { "id": "https://openalex.org/W3089899887", "doi": "10.1016/j.trc.2020.102813", "title": "The multiple flying sidekicks traveling salesman problem with variable drone speeds", "year": 2020, "publication_date": "2020-09-28", "type": "article", "language": "en", "authors": [ "Ritwik Raj", "Chase C. Murray" ], "first_author": "Ritwik Raj", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Truck", "Drone", "Computer science", "Range (aeronautics)", "Rendezvous", "Variable (mathematics)", "Fuel efficiency", "Simulation", "Automotive engineering", "Travelling salesman problem", "Real-time computing", "Engineering" ], "cited_by_count": 168, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2020.102813" }, { "id": "https://openalex.org/W3182067109", "doi": "10.1016/j.ejor.2021.07.008", "title": "The min-cost parallel drone scheduling vehicle routing problem", "year": 2021, "publication_date": "2021-07-10", "type": "article", "language": "en", "authors": [ "Minh Anh Nguyen", "Giang Thi-Huong Dang", "Minh Hoàng Hà", "Minh-Trien Pham" ], "first_author": "Minh Anh Nguyen", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Travelling salesman problem", "Computer science", "Vehicle routing problem", "Scheduling (production processes)", "Mathematical optimization", "Truck", "Job shop scheduling", "Routing (electronic design automation)", "Heuristic", "Integer programming", "Operations research" ], "cited_by_count": 157, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ejor.2021.07.008" }, { "id": "https://openalex.org/W4396910019", "doi": "10.1109/tro.2024.3400838", "title": "Autonomous Drone Racing: A Survey", "year": 2024, "publication_date": "2024-01-01", "type": "article", "language": "en", "authors": [ "Drew Hanover", "Antonio Loquercio", "Leonard Bauersfeld", "Ángel Romero", "Robert Pěnička", "Yunlong Song", "Giovanni Cioffi", "Elia Kaufmann", "Davide Scaramuzza" ], "first_author": "Drew Hanover", "venue": "IEEE Transactions on Robotics", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Over the last decade, the use of autonomous drone systems for surveying, search and rescue, or last-mile delivery has increased exponentially. With the rise of these applications comes the need for highly robust, safety-critical algorithms that can operate drones in complex and uncertain environments. Additionally, flying fast enables drones to cover more ground, increasing productivity and further strengthening their use case. One proxy for developing algorithms used in high-speed navigation is the task of autonomous drone racing, where researchers program drones to fly through a sequence of gates and avoid obstacles as quickly as possible using onboard sensors and limited computational power. Speeds and accelerations exceed over 80 kph and 4 g, respectively, raising significant challenges across perception, planning, control, and state estimation. To achieve maximum performance, systems require real-time algorithms that are robust to motion blur, high dynamic range, model uncertainties, aerodynamic disturbances, and often unpredictable opponents. This survey covers the progression of autonomous drone racing across model-based and learning-based approaches. We provide an overview of the field, its evolution over the years, and conclude with the biggest challenges and open questions to be faced in the future.", "keywords": [ "Drone", "Computer science", "Artificial intelligence", "Aeronautics", "Engineering", "Simulation", "Real-time computing" ], "cited_by_count": 135, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tro.2024.3400838" }, { "id": "https://openalex.org/W3112045312", "doi": "10.1016/j.cor.2020.105177", "title": "Designing a drone delivery network with automated battery swapping machines", "year": 2020, "publication_date": "2020-12-17", "type": "article", "language": "en", "authors": [ "Taner Cokyasar", "Wenquan Dong", "Mingzhou Jin", "İsmail Ömer Verbas" ], "first_author": "Taner Cokyasar", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Metropolitan area", "Key (lock)", "Service (business)", "Operations research", "Real-time computing", "Engineering", "Computer security", "Business" ], "cited_by_count": 55, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cor.2020.105177" }, { "id": "https://openalex.org/W4307078345", "doi": "10.1016/j.ejtl.2022.100094", "title": "Exact and heuristic approaches to Truck–Drone Delivery Problems", "year": 2022, "publication_date": "2022-10-22", "type": "article", "language": "en", "authors": [ "Júlia Cária de Freitas", "Puca Huachi Vaz Penna", "Túlio A. M. Toffolo" ], "first_author": "Júlia Cária de Freitas", "venue": "EURO Journal on Transportation and Logistics", "publisher": "Springer Science+Business Media", "abstract": "Collaborative delivery employing drones in last-mile delivery has been an extensively studied topic in recent years. In this paper, it is studied Truck–Drone Delivery Problems (TDDPs) in which a traditional delivery truck is gathered with a drone to cut delivery times and costs. The vehicles work together in a hybrid operation involving one drone launching from a larger vehicle that operates as a mobile depot and a recharging platform. The drone launches from the truck with a single package to deliver to a customer. Each drone must return to the truck to recharge batteries, pick up another package, and launch again to a new customer location. This work proposes a novel Mixed Integer Programming (MIP) formulation and a heuristic approach to address the problem. The proposed MIP formulation yields better linear relaxation bounds than previously proposed formulations for all instances, and was capable of optimally solving several unsolved instances from the literature. A hybrid heuristic based on the General Variable Neighborhood Search metaheuristic combining Tabu Search concepts is employed to obtain high-quality solutions for large-size instances. The efficiency of the algorithm was evaluated on 1415 benchmark instances from the literature, and over 80% of the best known solutions were improved.", "keywords": [ "Drone", "Truck", "Tabu search", "Benchmark (surveying)", "Computer science", "Metaheuristic", "Heuristic", "Mathematical optimization", "Integer programming", "Variable neighborhood search", "Engineering", "Operations research" ], "cited_by_count": 49, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S219243762200019X/pdf" }, { "id": "https://openalex.org/W3038034436", "doi": "10.3390/app10124362", "title": "Drone-Based Parcel Delivery Using the Rooftops of City Buildings: Model and Solution", "year": 2020, "publication_date": "2020-06-25", "type": "article", "language": "en", "authors": [ "Jun‐Su Kim", "Hongbin Moon", "Hosang Jung" ], "first_author": "Jun‐Su Kim", "venue": "Applied Sciences", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.", "keywords": [ "Drone", "Heuristic", "Computer science", "Computation", "Block (permutation group theory)", "City logistics", "Operations research", "Integer programming", "Mathematical optimization", "Transport engineering", "Engineering", "Artificial intelligence" ], "cited_by_count": 68, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2076-3417/10/12/4362/pdf" }, { "id": "https://openalex.org/W4301431241", "doi": "10.1016/j.pmcj.2022.101700", "title": "On the Scheduling of Conflictual Deliveries in a last-mile delivery scenario with truck-carried drones", "year": 2022, "publication_date": "2022-10-05", "type": "article", "language": "en", "authors": [ "Francesco Betti Sorbelli", "Federico Corò", "Sajal Kumar Das", "Lorenzo Palazzetti", "Cristina Maria Pinotti" ], "first_author": "Francesco Betti Sorbelli", "venue": "Pervasive and Mobile Computing", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Computer science", "Drone", "Mile", "Truck", "Last mile (transportation)", "Scheduling (production processes)", "Operations management", "Automotive engineering" ], "cited_by_count": 27, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.pmcj.2022.101700" }, { "id": "https://openalex.org/W3217657292", "doi": "10.1155/2021/2374955", "title": "Novel Spherical Fuzzy MARCOS Method for Assessment of Drone‐Based City Logistics Concepts", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Milovan Kovač", "Snežana Radoman Tadić", "Mladen Dragan Krstić", "Mouhamed Bayane Bouraima" ], "first_author": "Milovan Kovač", "venue": "Complexity", "publisher": "Hindawi Publishing Corporation", "abstract": "Technological innovations from the last few years, in the combination with city logistics (CL) initiatives, make the definition of novel, complex, sustainable CL solutions possible. Unmanned aerial vehicles (drones) as a technology attracted lots of attention in the literature. Various researches focused on different drone‐based delivery approaches, but there are only a few articles dealing with drones as the elements of complex CL concepts. The goal of this paper is to evaluate different drone‐based CL concepts. Based on the existing ideas of drone application in delivery, the main group of CL concepts and their variants are defined, which represents the main contribution of the article. The evaluation and ranking of concepts are performed from the aspect of all CL stakeholders and the defined set of criteria by applying measurement of alternatives and ranking according to compromise solution (MARCOS) multicriteria decision‐making (MCDM) method in spherical fuzzy environment, which represents another contribution of the article. The results indicate that the potentially best CL concept, with the final score of 0.408, is the one that refers to the transformation of the logistics system into a two‐echelon system with the implementation of micro‐consolidation centers (MCCs), in which the delivery of goods to MCCs is realized with rail transportation mode and the last delivery phase with drones. It is followed by the concepts that imply MCCs, and rail transportation in the function of mobile depots for drone launching and MCCs and ground delivery vehicles (GDVs), with the final scores of 0.395 and 0.390, respectively.", "keywords": [ "Drone", "Computer science", "Fuzzy logic", "Operations research", "Artificial intelligence", "Mathematics", "Biology" ], "cited_by_count": 78, "is_retracted": false, "is_paratext": false, "open_access_url": "https://downloads.hindawi.com/journals/complexity/2021/2374955.pdf" }, { "id": "https://openalex.org/W2910173889", "doi": "10.1007/s13272-020-00447-w", "title": "The acceptance of civil drones in Germany", "year": 2020, "publication_date": "2020-04-04", "type": "article", "language": "en", "authors": [ "Hinnerk Eißfeldt", "Verena Vogelpohl", "Michael C. Stolz", "Anne Papenfuß", "Marcus Biella", "Julie A. Belz", "Dirk Kügler" ], "first_author": "Hinnerk Eißfeldt", "venue": "CEAS Aeronautical Journal", "publisher": "Springer Science+Business Media", "abstract": "Abstract In recent years, civil drones have become more and more visible in everyday life. There are numerous reports in the media covering a variety of drone aspects and technical developments. In addition, everyone is used to bird’s-eye views as common features in television, movies and photography. However, little is known about how the public perceives this development. This article reports the results of a representative national study on the acceptance of civilian drones. Overall, a balanced but slightly positive attitude towards civil drones was revealed. Factors analyzed include age, gender, place of residence or interest in technical matters, as well as the individual level of knowledge about the topic. Free verbal associations with the general term drone are described as well as concerns about the usage of civil drones. Concerning different applications of civil drones, results indicate clear approval in Germany for the use of drones in civil protection, rescue missions and research work. However, flights for advertising, leisure and parcel delivery purposes are disagreed with by at least half of those questioned. In the presentation of the results, this article describes social acceptance of civilian drones and thus helps to better understand the perception of civil unmanned aerial vehicles.", "keywords": [ "Drone", "Perception", "Presentation (obstetrics)", "Variety (cybernetics)", "Political science", "Engineering", "Advertising", "Public relations", "Psychology", "Computer science", "Business", "Artificial intelligence" ], "cited_by_count": 113, "is_retracted": false, "is_paratext": false, "open_access_url": "https://link.springer.com/content/pdf/10.1007/s13272-020-00447-w.pdf" }, { "id": "https://openalex.org/W2567101652", "doi": "10.1016/j.trpro.2016.12.088", "title": "Replicators, Ground Drones and Crowd Logistics A Vision of Urban Logistics in the Year 2030", "year": 2016, "publication_date": "2016-01-01", "type": "article", "language": "en", "authors": [ "Oliver Kunze" ], "first_author": "Oliver Kunze", "venue": "Transportation research procedia", "publisher": "Elsevier BV", "abstract": "How will logistics in cities be carried out in the midterm future? To answer this question an overview of different existing and emerging transport logistics operations is provided, the pros and cons of these different operations are set out. Based on these findings a partial qualitative systemic model is presented which shows how these operations are influenced by global and logistics trends on the one hand and by delivery service requirements on the other hand. Based on this model a vision of urban logistics in Europe in the year 2030 as well as the concept of “Post 4.0” is presented.", "keywords": [ "Drone", "City logistics", "Service (business)", "Humanitarian Logistics", "Set (abstract data type)", "Business", "Computer science", "Transport engineering", "Process management", "Operations research", "Operations management", "Marketing" ], "cited_by_count": 79, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S2352146516308742/pdf" }, { "id": "https://openalex.org/W4206860618", "doi": "10.1016/j.trb.2023.01.004", "title": "Freight-on-Transit for urban last-mile deliveries: A strategic planning approach", "year": 2023, "publication_date": "2023-02-07", "type": "article", "language": "en", "authors": [ "Diego Delle Donne", "Laurent Alfandari", "Claudia Archetti", "Ivana Ljubić" ], "first_author": "Diego Delle Donne", "venue": "Transportation Research Part B Methodological", "publisher": "Elsevier BV", "abstract": "We study a delivery strategy for last-mile deliveries in urban areas which combines freight transportation with mass mobility systems with the goal of creating synergies contrasting negative externalities caused by transportation. The idea is to use the residual capacity on public transport means for moving freight within the city. In particular, the system is such that parcels are first transported from origins (central distribution centers) to drop-in stations, which are stop locations on public vehicle itineraries. Then, they are transported on public vehicles to drop-out stations, from where they are delivered to destination by green vehicles (such as bikes, drones, porters, etc.). The system is known as Freight-On-Transit (FOT). In this paper, we focus on the strategic decisions related to defining the public transportation network that will take part in the delivery system, i.e., which public vehicle lines and stop locations will be included (and thus equipped for the service). We propose different formulations for the problem and effective heuristic solution approaches based on column generation. We perform exhaustive tests aimed at providing managerial insights on the performance and the efficiency of the system.", "keywords": [ "Mile", "Transit (satellite)", "Transport engineering", "Last mile (transportation)", "Business", "Strategic planning", "Urban transit", "Transit system", "Transportation planning", "Environmental planning", "Geography", "Public transport" ], "cited_by_count": 55, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trb.2023.01.004" }, { "id": "https://openalex.org/W3129292331", "doi": "10.1016/j.ejor.2021.02.022", "title": "Ground-vehicle and unmanned-aerial-vehicle routing problems from two-echelon scheme perspective: A review", "year": 2021, "publication_date": "2021-02-16", "type": "article", "language": "en", "authors": [ "Hongqi Li", "Jun Chen", "Feilong Wang", "Ming Bai" ], "first_author": "Hongqi Li", "venue": "European Journal of Operational Research", "publisher": "Elsevier BV", "abstract": "More and more studies have aimed to optimize the ground vehicle (GV) and unmanned aerial vehicle (UAV) system in which GVs function as mobile satellites and UAVs are dispatched from GVs for last-mile deliveries. From the two-echelon scheme perspective, GV routes originating at the depot are on one echelon, and UAV routes originating at satellites are on the other echelon. A change in a GV route may affect some UAV routes, which indicates the satellite synchronization. In the past decade, the optimization of vehicle routes in two-echelon networks has attracted increasing attention in the operations research community. We classify routing problems of two-echelon networks based on the modeling mechanism connecting the two echelons. Different formulations for describing connection mechanisms of the two-echelon scheme, especially constraints on capacitated satellites, satellite synchronization, vehicle coupling/decoupling at satellites, etc., are briefly introduced. There are several modeling challenges of optimizing delivery routes for a fleet of GV–UAV combinations that include new connection mechanisms between the two echelons. Some important variants, especially those involving mobile satellite synchronization, and GV–UAV flexibly coupling/decoupling, require new mathematical formulations and algorithms catering to more general and practical situations.", "keywords": [ "Computer science", "Decoupling (probability)", "Synchronization (alternating current)", "Scheme (mathematics)", "Perspective (graphical)", "Real-time computing", "Operations research", "Distributed computing", "Computer network", "Engineering", "Artificial intelligence", "Control engineering" ], "cited_by_count": 147, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S0377221721001156/pdf" }, { "id": "https://openalex.org/W4386745731", "doi": "10.1080/00207543.2023.2254402", "title": "Delivery network design of a locker-drone delivery system", "year": 2023, "publication_date": "2023-09-14", "type": "article", "language": "en", "authors": [ "Bipan Zou", "Siqing Wu", "Yeming Gong", "Zhe Yuan", "Yuqian Shi" ], "first_author": "Bipan Zou", "venue": "International Journal of Production Research", "publisher": "Taylor & Francis", "abstract": "Drones are increasingly used for last-mile delivery due to their speed and cost-effectiveness. This study focuses on a novel locker-drone delivery system, where trucks transport parcels from the warehouse to lockers, and drones complete the final delivery. This system is ideal for community and intra-facility logistics. The research optimises the network design by determining the location of lockers, the number of drones at each locker, and the assignment of demands to lockers, minimising operating costs. Both single-parcel and multi-parcel capacity drones are examined. We build an optimisation model for each system, considering drone service capacity as a critical constraint. We design an algorithm combining average sample approximation and a genetic algorithm to address demand uncertainty. The algorithm's efficiency is validated through comparative analysis with Gurobi. Numerical experiments, using real and generated data, optimise the network design. Results show that the multi-capacity drone system requires fewer lockers and drones than the single-capacity system. Although the single-capacity system yields lower drone delivery costs, it incurs higher truck delivery costs. Additionally, a comprehensive cost analysis compares the cost-efficiency of the locker-drone system with a conventional drone delivery system, revealing the cost-saving advantage of the locker-drone system.", "keywords": [ "Drone", "Truck", "Last mile (transportation)", "Computer science", "Operations research", "Engineering", "Simulation", "Transport engineering", "Automotive engineering", "Mile", "Geography" ], "cited_by_count": 45, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/00207543.2023.2254402" }, { "id": "https://openalex.org/W2943166133", "doi": "10.1016/j.cor.2019.04.021", "title": "A hybrid VNS/Tabu search algorithm for solving the vehicle routing problem with drones and en route operations", "year": 2019, "publication_date": "2019-05-01", "type": "article", "language": "en", "authors": [ "Daniel Schermer", "Mahdi Moeini", "Oliver Wendt" ], "first_author": "Daniel Schermer", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Tabu search", "Computer science", "Variable neighborhood search", "Solver", "Drone", "Vehicle routing problem", "Mathematical optimization", "Integer programming", "Routing (electronic design automation)", "Heuristic", "Job shop scheduling", "Local search (optimization)" ], "cited_by_count": 271, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cor.2019.04.021" }, { "id": "https://openalex.org/W3206138165", "doi": "10.1109/access.2021.3120347", "title": "A Path-Following Controller for a UAV-UGV Formation Performing the Final Step of Last-Mile-Delivery", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Vinícius Pacheco Bacheti", "Alexandre Santos Brandao", "Mário Sarcinelli-Filho" ], "first_author": "Vinícius Pacheco Bacheti", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "This work discusses the accomplishment of a path-following task by a formation of an unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV). The idea behind such an application is that the UAV is returning after delivering a package, and should land on the UGV, its reference base, which continues following its route towards another delivery. A high level controller based on the virtual structure paradigm is designed to guide the formation, which also includes an obstacle avoidance algorithm to handle the possibility that the UGV, the reference for the formation, faces an obstacle in its path, such as another vehicle, for instance. After describing in details the controller designed and the obstacle avoidance algorithm, simulated and experimental results are shown and discussed, which validate the proposed controller.", "keywords": [ "Unmanned ground vehicle", "Computer science", "Obstacle", "Obstacle avoidance", "Controller (irrigation)", "Path (computing)", "Base (topology)", "Task (project management)", "Real-time computing", "Simulation", "Artificial intelligence", "Mobile robot" ], "cited_by_count": 42, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/access.2021.3120347" }, { "id": "https://openalex.org/W2910984544", "doi": "10.1016/j.trc.2019.01.006", "title": "Parcel delivery in urban areas: Opportunities and threats for the mix of traditional and green business models", "year": 2019, "publication_date": "2019-01-11", "type": "article", "language": "en", "authors": [ "Guido Perboli", "Mariangela Rosano" ], "first_author": "Guido Perboli", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Business", "Business model", "Environmental planning", "Business Model Canvas", "Marketing", "Geography" ], "cited_by_count": 209, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2019.01.006" }, { "id": "https://openalex.org/W4282925682", "doi": "10.1016/j.tre.2022.102788", "title": "Collaborative truck multi-drone routing and scheduling problem: Package delivery with flexible launch and recovery sites", "year": 2022, "publication_date": "2022-06-15", "type": "article", "language": "en", "authors": [ "Mohamed Salama", "Sharan Srinivas" ], "first_author": "Mohamed Salama", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Scheduling (production processes)", "Computer science", "Vehicle routing problem", "Job shop scheduling", "Simulated annealing", "Exploit", "Integer programming", "Routing (electronic design automation)", "Operations research", "Real-time computing" ], "cited_by_count": 195, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2022.102788" }, { "id": "https://openalex.org/W2985457092", "doi": "10.1108/eemcs-06-2018-0150", "title": "Feasibility of drone integration as last mile delivery", "year": 2019, "publication_date": "2019-11-04", "type": "article", "language": "en", "authors": [ "Sadia Samar Ali", "Supriya Deka", "Zulfiqar Ahmad", "Salma Badawi Mohammed Ahmed", "Mansingh Jaswal", "Hemaid Alsulami" ], "first_author": "Sadia Samar Ali", "venue": "Emerald Emerging Markets Case Studies", "publisher": "Emerald Publishing Limited", "abstract": "Supplementary materials Padmanabhan A. 2017 “Civilian drones and India’s regulatory response”. Moushami P. Joshi and Jennifer E. Trock (2016) “India Moving Forward with Unmanned Aircraft Systems Regulations for Civil and Commercial Use” www.lexology.com/library/detail.aspx?g=6d596577-7a4a-4ecc-916e-83c4d37cc90c . www.indrones.com/2017/04/27/drone-industry-india/.Zeimpekis , Vasileios; Ichoua, Soumia; and Minis, Ioannis (2013), Humanitarian and Relief Logistics. Research Issues, Case Studies and Future Trends;Operations Research/Computer Sciences Interfaces Series. Springer Publications, www.springer.com/in/book/9781461470069 . Learning outcomes The learning outcomes are to illustrate the concept and features of cost-effective and responsive supply chain, to explain the concept of hub and spoke and milk run methods used for delivery, to identify financial, operational and technological risks, to elaborate the importance of social dimension (behavioral dimension) in any technological change in an organization and to understand the concept of management of change in organizations. Case overview/synopsis The case deals with a typical challenge of periodical delivery systems, in this case specifically of The Topical, an Indian periodical. The service manager of the company, Sara Jindal, recognized a problem with customer retention. She explored the causes and found that The Topical, a 20-year-old company, was losing its popularity due to the untimely delivery of the magazines. To solve the problem Jindal, tried to gain an understanding of the operational processes and realized that there was no issue in the warehouse regarding inventory control, management or order pickup. However, she found that the magazines were parceled through book post and that there was no tracking policy in the company for the deliveries. Therefore, it was not possible to know whether the magazines got delivered on time. The matter was taken seriously and as a solution, the possibility of integrating drones into the delivery system came up. Complexity academic level Undergraduate and Postgraduate students. Subject code CSS 9: Operations and Logistics", "keywords": [ "Drone", "Popularity", "Last mile (transportation)", "Dimension (graph theory)", "Order (exchange)", "Marketing", "Business", "Service (business)", "Supply chain", "Operations research", "Political science", "Engineering" ], "cited_by_count": 15, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1108/eemcs-06-2018-0150" }, { "id": "https://openalex.org/W3006539294", "doi": null, "title": "Drone Delivery: Urban airspace traffic density estimation", "year": 2018, "publication_date": "2018-01-01", "type": "conference-paper", "language": "en", "authors": [ "Malik Doole", "Joost Ellerbroek", "Jacco M. Hoekstra" ], "first_author": "Malik Doole", "venue": "Data Archiving and Networked Services (DANS)", "publisher": "Royal Netherlands Academy of Arts and Sciences", "abstract": "The concept of autonomous drone delivery in urban areas has gained a favorable amount of media attention over the past few years. Companies such as Amazon, Uber and Matternet are investigating the use of drones to transport parcels in order to solve the disaggregate delivery (last-mile) problem. This solution could potentially reduce vehicular congestion in cities by replacing traditional transport modes used in last-mile delivery, such as trucks, vans and bikes, with a fleet of autonomous drones flying in an urban airspace. To realize this concept, the design of an urban airspace for drones is necessary. However, the design of an urban airspace for drones will depend on critical design metrics such as drone traffic densities, traffic distribution patterns, distance between origin-destination, and the number of distribution centers. For this study, we first tackle the first metric, drone traffic density. This metric will provide an indication for the required urban airspace capacity and its expected demand. This paper therefore establishes a framework for determining the traffic density of delivery drones for a typical urban city airspace in Europe. In addition, the paper presents a cost-analysis study for fast-food delivery via drones relative to electric bikes.", "keywords": [ "Drone", "Transport engineering", "Last mile (transportation)", "Mile", "Computer science", "Metric (unit)", "Truck", "Geography", "Engineering", "Automotive engineering", "Operations management" ], "cited_by_count": 40, "is_retracted": false, "is_paratext": false, "open_access_url": "http://resolver.tudelft.nl/uuid:f33c73a1-683f-4f9d-a04a-55254dd4aebf" }, { "id": "https://openalex.org/W4366308858", "doi": "10.1109/tits.2023.3266460", "title": "A-VRPD: Automating Drone-Based Last-Mile Delivery Using Self-Driving Cars", "year": 2023, "publication_date": "2023-04-18", "type": "article", "language": "en", "authors": [ "Navid Mohammad Imran", "Sabyasachee Mishra", "Myounggyu Won" ], "first_author": "Navid Mohammad Imran", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Drone-based last-mile delivery is an emerging technology that uses drones loaded onto a truck to deliver parcels to customers. In this paper, we introduce a fully automated system for drone-based last-mile delivery through incorporation of autonomous vehicles (AVs). A novel problem called the autonomous vehicle routing problem with drones (A-VRPD) is defined. A-VRPD is to select AVs from a pool of available AVs based on crowd sourcing, assign selected AVs to customer groups, and schedule routes for selected AVs to optimize the total operational cost. We formulate A-VRPD as a Mixed Integer Linear Program (MILP) and propose an optimization framework to solve the problem. A greedy algorithm is also developed to significantly improve the running time for large-scale delivery scenarios. Extensive simulations were conducted taking into account real-world operational costs for different types of AVs, traveled distances calculated considering the real-time traffic conditions using Google Map API, and varying load capacities of AVs. We evaluated the performance in comparison with two different state-of-the-art solutions: an algorithm designed to address the traditional vehicle routing problem with drones (VRP-D), which involves human-operated trucks working in tandem with drones to deliver parcels, and an algorithm for the two echelon vehicle routing problem (2E-VRP), wherein parcels are first transported to satellite locations and subsequently delivered from those satellites to the customers. The results indicate a substantial increase in profits for both the delivery company and vehicle owners compared with the state-of-the-art algorithms.", "keywords": [ "Drone", "Vehicle routing problem", "Truck", "Last mile (transportation)", "Computer science", "Schedule", "Real-time computing", "Routing (electronic design automation)", "Integer programming", "Linear programming", "Mile", "Transport engineering" ], "cited_by_count": 26, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2023.3266460" }, { "id": "https://openalex.org/W2887654240", "doi": "10.21078/jssi-2018-302-18", "title": "Application of Drone in Solving Last Mile Parcel Delivery", "year": 2018, "publication_date": "2018-08-13", "type": "article", "language": "en", "authors": [ "Jiashi Liu", "Zhongliang Guan", "Jennifer S. Shang", "Xiang Xie" ], "first_author": "Jiashi Liu", "venue": "系统科学与信息学报(英文)", "publisher": null, "abstract": "Abstract The article is about solving the last mile delivery problem in rural town or village. We want to test the drone’s potential in parcel delivery. The objectives are 1) to introduce the cluster and truck-drone in tandem delivery method, 2) to compare the new method with the traditional TSP method in aspect of truck running distance, energy using and time occupation. The parcel delivery demand is sparse, so it is not dense enough for a truck to carry on delivery. We try to identify the best route for the drone to deliver the goods. We use k-mean method to carry on clustering, then we use enumeration method to fulfill the centroids delivery, which comes from the depot. We design a model and calculate the energy, time and distance saving between drone using method (DTSP) and traditional TSP method. The drone attended delivery saves truck delivery distance, energy consumption and time. The truck running distance of DTSP method saves 91.87%, the truck running distance is shortened from 189.69 km to 15.4252 km. The DTSP method saves 90.45% of energy. The DTSP method brings a 29.75% cutoff in time aspect when there are two drone in running. The research introduces the cluster and TSP combination method, which is a good way to carry on last mile delivery. The result shows a bright future for drone to attend parcel delivery. The e-commerce corporation can apply this method in practice.", "keywords": [ "Drone", "Truck", "Last mile (transportation)", "Computer science", "Cluster analysis", "Mile", "Cluster (spacecraft)", "Operations research", "Simulation", "Engineering", "Artificial intelligence", "Automotive engineering" ], "cited_by_count": 8, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.21078/jssi-2018-302-18" }, { "id": "https://openalex.org/W3215148040", "doi": "10.1016/j.cor.2022.106112", "title": "The vehicle routing problem with drones and drone speed selection", "year": 2022, "publication_date": "2022-12-05", "type": "article", "language": "en", "authors": [ "Felix Tamke", "Udo Buscher" ], "first_author": "Felix Tamke", "venue": "Computers & Operations Research", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Computer science", "Energy consumption", "Fuel efficiency", "Routing (electronic design automation)", "Operations research", "Automotive engineering", "Engineering" ], "cited_by_count": 94, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cor.2022.106112" }, { "id": "https://openalex.org/W4394841325", "doi": "10.1080/13675567.2024.2341851", "title": "Consumers’ perceptions of the environmental and public health benefits of last mile drone delivery", "year": 2024, "publication_date": "2024-04-16", "type": "article", "language": "en", "authors": [ "Steven Leon", "Charlie Chen", "Aaron Ratcliffe" ], "first_author": "Steven Leon", "venue": "International Journal of Logistics Research and Applications", "publisher": "Taylor & Francis", "abstract": "Using Technology Acceptance Model, Theory of Planned Behavior, and Privacy Calculus as theoretical frameworks, this study examined environmental and public health/safety dispositions and environmental and public health/safety benefits, perceived usefulness, privacy risk, and trust as they relate to U.S consumers intention to adopt drone delivery services. This study employed Partial Least Squares – Structural Equation Modeling methods and data were collected online using Amazon Mechanical Turk, resulting in 687 respondents. The results show that the intention to use drones for delivery increases if consumers perceive drone delivery to be useful. Additionally, perceived usefulness was influenced by a person’s environmental and public health/safety dispositions along with related benefits. Additionally, as a person’s perceived usefulness increases their perceived privacy risk decreases. Further, this study found that organisational trust moderates the negative effect of privacy risk on drone adoption.", "keywords": [ "Drone", "Structural equation modeling", "Risk perception", "Perception", "Public health", "Mile", "Psychology", "Business", "Environmental health", "Health belief model", "Last mile (transportation)", "Applied psychology" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/13675567.2024.2341851" }, { "id": "https://openalex.org/W4312800397", "doi": "10.1109/tase.2022.3213254", "title": "Drone Stations-Aided Beyond-Battery-Lifetime Flight Planning for Parcel Delivery", "year": 2022, "publication_date": "2022-10-13", "type": "article", "language": "en", "authors": [ "Chao Huang", "Zhenxing Ming", "Hailong Huang" ], "first_author": "Chao Huang", "venue": "IEEE Transactions on Automation Science and Engineering", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "This paper considers using drones to conduct the last-mile parcel delivery. To enable the beyond-battery-lifetime flight, drone stations are considered to replace or recharge the battery for drones. We focus on the flight planning problem with the goal of minimizing the total travel time from the depot to a customer, a key indicator of the quality of service. We investigate four typical ways for the drone to get extra energy at drone stations: 1) replacing the battery with a fresh one, 2) recharging the battery to the full capacity, 3) recharging the battery to the optimal level, and 4) recharging the battery to the optimal level accounting for the availability of drone stations (i.e., whether a drone station is occupied by other drones). While the first two scenarios can be formulated following the framework of integer linear programming, the last two scenarios turn into mixed-integer nonlinear programming problems. To address the later problems, we present a framework in which discretized state graphs are constructed first and then the optimal paths are found by graph searching algorithms. We propose a dynamic version of Dijkstra’s algorithm to deal with the unavailability issue of drone stations. The algorithm can quickly find the optimal flight path for a drone, and extensive computer-based experimental results have been presented to demonstrate the effectiveness of the proposed method. Note to Practitioners—Multi-rotary unmanned aerial vehicles (UAVs), also known as drones, have been regarded as a promising means to reshape future logistics. To save human labour and reduce cost, many giant logistics companies have been dedicated to developing various drones to deliver light and small parcels during the past decade. However, due to the limitation of payload, the battery capacity is constrained, which prevents drones from long-distance flights. Practitioners have tried the drone-vehicle collaboration method, but this still requires human labour to participate. In this paper, we present a framework where drones autonomously conduct long-distance delivery with the assistance of drone stations. It is worth pointing out that such a framework is not to replace the ground delivery method but to serve as an alternative to the ground counterpart for small and light parcels. A particular focus is on the flight planning from the depot to a destination, which includes not only a sequence of drone stations to stop at but also the corresponding rest time to recharge the battery. Several typical scenarios about battery recharging are discussed, and a dynamic version of Dijkstra’s algorithm is presented to deal with the challenging case where drone station resources are limited. The presented approach is able to find out the optimal flight plan quickly.", "keywords": [ "Drone", "Unavailability", "Computer science", "Battery (electricity)", "Real-time computing", "Integer programming", "Operations research", "Engineering", "Reliability engineering", "Algorithm" ], "cited_by_count": 48, "is_retracted": false, "is_paratext": false, "open_access_url": "http://ira.lib.polyu.edu.hk/bitstream/10397/98854/1/Huang_Drone_Flight_Planning.pdf" }, { "id": "https://openalex.org/W4310355642", "doi": "10.1016/j.tre.2022.102967", "title": "Robust traveling salesman problem with multiple drones: Parcel delivery under uncertain navigation environments", "year": 2022, "publication_date": "2022-11-25", "type": "article", "language": "en", "authors": [ "Lei Zhao", "Xinhua Bi", "Gendao Li", "Zhaohui Dong", "Ni Xiao", "Anni Zhao" ], "first_author": "Lei Zhao", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Travelling salesman problem", "Drone", "Computer science", "Traveling purchaser problem", "2-opt", "Operations research", "Simulation", "Engineering", "Biology" ], "cited_by_count": 54, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2022.102967" }, { "id": "https://openalex.org/W4407409353", "doi": "10.1016/j.ecotra.2025.100398", "title": "Drone-as-a-Service for last-mile delivery: Evidence of economic viability", "year": 2025, "publication_date": "2025-02-12", "type": "article", "language": "en", "authors": [ "Evangelia Filiopoulou", "Cleopatra Bardaki", "Μάρα Νικολαϊδου", "Christos Michalakelis" ], "first_author": "Evangelia Filiopoulou", "venue": "Economics of Transportation", "publisher": "Elsevier BV", "abstract": "An economic viability of last-mile delivery via drones is assessed, offering an investment model comparing traditional motorcycle delivery to drone-based alternatives. Two drone investment options — purchase or lease (Drone-as-a-Service) — were introduced. The proposed last-mile delivery model considers capital and operational costs, calculating Net Present Value(NPV) and Return of Investment (ROI) per investment scenario. For the operational expenses, the energy consumption model for the motorcycle and the drone is formulated. Furthermore, three wind settings — low, medium, and high wind — were examined to account for environmental factors impacting drone performance. The investment model has been formulated and then validated considering the relevant literature as well as realistic information collected during a semi-structured interview with industry experts The findings affirm the financial feasibility of adopting drones for last-mile delivery. Drone-as-a-Service emerged as a more profitable choice, exhibiting improved NPV and ROI over owned drones or motorcycle delivery. Emphasizing DaaS in the investment model presents a probable scenario for the logistics industry, easing their transition to drone technology. Evidence of DaaS viability is of value since it could convince risk-averse distribution vendors to adopt drone delivery .", "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Service (business)", "Business", "Transport engineering", "Engineering", "Computer security", "Computer science", "Marketing", "Geography", "Biology" ], "cited_by_count": 17, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.ecotra.2025.100398" }, { "id": "https://openalex.org/W4386501103", "doi": "10.1016/j.trc.2023.104316", "title": "Centralized supply chain network optimization with UAV-based last mile deliveries", "year": 2023, "publication_date": "2023-09-07", "type": "article", "language": "en", "authors": [ "Gabriella Colajanni", "Patrizia Daniele", "Anna Nagurney" ], "first_author": "Gabriella Colajanni", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": "This paper proposes a centralized supply chain network optimization model that maximizes the total profit obtained by a company that produces and/or outsources production, stores, ships and sells products to customers using a fleet made up of trucks and, in the last mile, also of drones. The model includes realistic features of unmanned aerial vehicles (UAVs) in the form of drones with fundamental limitations such as low battery capacities and short delivery ranges. The constrained nonlinear optimization problem is formulated as a variational inequality. Existence and uniqueness results for the solution of the variational inequality are provided along with the results of detailed numerical simulations that emphasize the advantages of the use of a hybrid fleet from enhanced profits to reduction in air pollution. Our quantitative results reveal great promise and insights for the logistics industry in the use of emerging UAV technologies for last mile parcel deliveries as a practical solution within a holistic supply chain network context.", "keywords": [ "Last mile (transportation)", "Drone", "Truck", "Supply chain", "Profit (economics)", "Context (archaeology)", "Supply chain network", "Variational inequality", "Computer science", "Operations research", "Nonlinear programming", "Mile" ], "cited_by_count": 27, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2023.104316" }, { "id": "https://openalex.org/W4399209191", "doi": "10.1016/j.trb.2024.102970", "title": "Hybrid truck–drone delivery under aerial traffic congestion", "year": 2024, "publication_date": "2024-05-31", "type": "article", "language": "en", "authors": [ "Ruifeng She", "Yanfeng Ouyang" ], "first_author": "Ruifeng She", "venue": "Transportation Research Part B Methodological", "publisher": "Elsevier BV", "abstract": "This paper focuses on a hybrid truck–drone delivery system, in which a truck carries goods and a fleet of drones around the neighborhoods of customers, while the drones are dispatched from the truck to perform the last-mile delivery. We formulate a continuous traffic equilibrium model in the form of partial differential equations (PDEs) to describe the optimal drone routing and truck–drone synchronization strategies when low-altitude aerial traffic congestion arises in large-scale steady-state operations. A customized solution algorithm is then developed, using a physics-informed neural network framework and various enhancement techniques, to efficiently solve the PDEs. The PDE solution is then used to evaluate the operational cost of a truck–drone delivery system, through a dimensionless surrogate model, which further provides the basis for optimizing several service design decisions, such as truck speed, truck routing plan and delivery headway. Numerical experiments are conducted to show the applicability of the proposed modeling framework, and to draw managerial insights for logistics carriers.", "keywords": [ "Drone", "Truck", "Traffic congestion", "Transport engineering", "Computer science", "Aeronautics", "Engineering", "Automotive engineering", "Biology" ], "cited_by_count": 44, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trb.2024.102970" }, { "id": "https://openalex.org/W2972415844", "doi": "10.1002/jia2.25337", "title": "Monitoring viral load for the last mile: what will it cost?", "year": 2019, "publication_date": "2019-09-01", "type": "article", "language": "en", "authors": [ "Brooke E Nichols", "Sarah J. Girdwood", "Thomas Crompton", "Lynsey Stewart‐Isherwood", "Leigh Berrie", "Dorman Chimhamhiwa", "Crispin Moyo", "John Kuehnle", "Wendy Susan Stevens", "Sydney B. Rosen", "EQUIP Health" ], "first_author": "Brooke E Nichols", "venue": "Journal of the International AIDS Society", "publisher": "International AIDS Society", "abstract": "INTRODUCTION: Routine viral load testing is the WHO-recommended method for monitoring HIV-infected patients on ART, and many countries are rapidly scaling up testing capacity at centralized laboratories. Providing testing access to the most remote populations and facilities (the \"last mile\") is especially challenging. Using a geospatial optimization model, we estimated the incremental costs of accessing the most remote 20% of patients in Zambia by expanding the transportation network required to bring blood samples from ART clinics to centralized laboratories and return results to clinics. METHODS: The model first optimized a sample transportation network (STN) that can transport 80% of anticipated sample volumes to centralized viral load testing laboratories on a daily or weekly basis, in line with Zambia's 2020 targets. Data incorporated into the model included the location and infrastructure of all health facilities providing ART, location of laboratories, measured distances and drive times between the two, expected future viral load demand by health facility, and local cost estimates. We then continued to expand the modelled STN in 5% increments until 100% of all samples could be collected. RESULTS AND DISCUSSION: The cost per viral load test when reaching 80% patient volumes using centralized viral load testing was a median of $18.99. With an expanded STN, the incremental cost per test rose to $20.29 for 80% to 85% and $20.52 for 85% to 90%. Above 90% coverage, the incremental cost per test increased substantially to $31.57 for 90% to 95% and $51.95 for 95% to 100%. The high numbers of kilometres driven per sample transported and large number of vehicles needed increase costs dramatically for reaching the clinics that serve the last 5% of patients. CONCLUSIONS: Providing sample transport services to the most remote clinics in low- and middle-income countries is likely to be cost-prohibitive. Other strategies are needed to reduce the cost and increase the feasibility of making viral load monitoring available to the last 10% of patients. The cost of alternative methods, such as optimal point-of-care viral load equipment placement and usage, dried blood/plasma spot specimen utilization, or use of drones in geographically remote facilities, should be evaluated.", "keywords": [ "Viral load", "Medicine", "Geospatial analysis", "Sample (material)", "Mile", "Test (biology)", "Operations management", "Operations research", "Human immunodeficiency virus (HIV)", "Virology", "Engineering" ], "cited_by_count": 40, "is_retracted": false, "is_paratext": false, "open_access_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/jia2.25337" }, { "id": "https://openalex.org/W3018743220", "doi": "10.1016/j.techsoc.2020.101262", "title": "Understanding the structure of risk belief systems concerning drone delivery: A network analysis", "year": 2020, "publication_date": "2020-04-22", "type": "article", "language": "en", "authors": [ "Xun Zhu", "Timothy J. Pasch", "Aaron Bergstrom" ], "first_author": "Xun Zhu", "venue": "Technology in Society", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Risk perception", "Leverage (statistics)", "Risk management", "Business", "Risk analysis (engineering)", "Perception", "Public relations", "Marketing", "Psychology", "Political science", "Computer science" ], "cited_by_count": 55, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.techsoc.2020.101262" }, { "id": "https://openalex.org/W3039186801", "doi": null, "title": "Drone Deliveries Logistics, Efficiency, Safety and Last Mile Trade-offs", "year": 2018, "publication_date": "2018-01-01", "type": "article", "language": "en", "authors": [ "Miguel Figliozzi", "Chad J. Tucker", "Polina Polikakhina" ], "first_author": "Miguel Figliozzi", "venue": "PDXScholar (Portland State University)", "publisher": "Portland State University", "abstract": "Unmanned aerial vehicles (UAV) or drone last mile deliveries are receiving a lot of attention from startups and big companies like Google, Amazon, and UPS. Around the world there are already examples of successful small scale delivery operations utilizing drones. Despite all the hype and excitement around this topic, there is surprisingly little research done on understanding the capabilities and technical tradeoffs among drones that are currently available in the market. The goal of this paper is to survey currently available multicopter drones and analyze them in terms of their potential for last mile and last yard deliveries. Novel data and linear relationships among multicopter payload, take-off weight, and energy efficiency are presented. A novel contribution of this research is the discussion of tradeoffs among UAV logistical capabilities, sustainability, safety, and last yard delivery constraints.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "Business", "Transport engineering", "Engineering", "Geography" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://pdxscholar.library.pdx.edu/cengin_fac/553" }, { "id": "https://openalex.org/W4391169862", "doi": "10.3390/math12030367", "title": "Assessing Strategies to Overcome Barriers for Drone Usage in Last-Mile Logistics: A Novel Hybrid Fuzzy MCDM Model", "year": 2024, "publication_date": "2024-01-23", "type": "article", "language": "en", "authors": [ "Snežana Radoman Tadić", "Mladen Dragan Krstić", "Ljubica Radovanović" ], "first_author": "Snežana Radoman Tadić", "venue": "Mathematics", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Effective last-mile (LM) delivery is critical to the efficient functioning of supply chains. In addition to speed and the cost of delivery, environmental and social sustainability are increasingly important factors in last-mile logistics (LML), especially in urban areas. Sustainable solutions such as drones attract special attention from researchers due to their high potential. The future of drone logistics is uncertain due to many barriers. This study analyzes, evaluates and ranks barriers to identify those that most significantly hinder broader drone adoption in LML, and proposes and ranks strategies to overcome them. This type of issue requires the involvement of multiple stakeholders with conflicting goals and interests. Therefore, the study employs a novel hybrid multi-criteria decision-making (MCDM) model that combines fuzzy Delphi-based fuzzy factor relationship (Fuzzy D-FARE) and fuzzy comprehensive distance-based ranking (Fuzzy COBRA) methods. The results indicate that the main obstacle to drone implementation in LM is the lack of aviation regulations. The risks of unauthorized access, data misuse, privacy breaches, and data security represent significant challenges. They are followed by ambiguously defined or burdensome requirements for insurance and liability for drone owners. The main contributions of this study are the establishment of a novel hybrid model, identification and ranking of barriers for broader application of drones in LML, and strategies for overcoming them.", "keywords": [ "Multiple-criteria decision analysis", "Drone", "Mile", "Fuzzy logic", "Last mile (transportation)", "Computer science", "Operations research", "Engineering", "Artificial intelligence", "Geography" ], "cited_by_count": 32, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2227-7390/12/3/367/pdf?version=1706023066" }, { "id": "https://openalex.org/W4321073941", "doi": "10.1016/j.jnca.2023.103601", "title": "A matching game-based crowdsourcing framework for last-mile delivery: Ground-vehicles and Unmanned-Aerial Vehicles", "year": 2023, "publication_date": "2023-02-16", "type": "article", "language": "en", "authors": [ "Huda Abualola", "Rabeb Mizouni", "Hadi Otrok", "Shakti Singh", "Hassan Barada" ], "first_author": "Huda Abualola", "venue": "Journal of Network and Computer Applications", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Crowdsourcing", "Computer science", "Task (project management)", "Last mile (transportation)", "Matching (statistics)", "Scheduling (production processes)", "Operations research", "Real-time computing", "Mile", "Operations management", "Engineering", "Systems engineering" ], "cited_by_count": 22, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.jnca.2023.103601" }, { "id": "https://openalex.org/W4401460846", "doi": "10.1111/itor.13527", "title": "Optimal drone deployment for cost‐effective and sustainable last‐mile delivery operations", "year": 2024, "publication_date": "2024-08-09", "type": "article", "language": "en", "authors": [ "Gaurav Kumar", "Oqais Tanvir", "Akhilesh Kumar", "Mohit Goswami" ], "first_author": "Gaurav Kumar", "venue": "International Transactions in Operational Research", "publisher": "Wiley", "abstract": "Abstract Delivery by drones holds significant potential to solve issues (such as high costs, access to remote areas, etc.) faced in last‐mile delivery operations, particularly in the e‐commerce industry. Still, it involves complex issues such as multi‐trip operations, energy estimation, and battery recharge planning. A sound drone delivery problem entails an optimal drone deployment plan with routing details at the lowest possible cost. To this end, this study focuses on formulating a delivery problem that involves multi‐trip drone routing, energy optimization, and travel time optimization problems where energy consumption by drones is modeled as a non‐linear function. We develop a mixed integer non‐linear programming model as an integrated optimization model. This model aims to: (a) maximize revenue by meeting demand completely without leaving idle drones, (b) optimize energy use by drones, and (c) minimize the required drone fleet size for an optimal plan. The proposed model is solved using the Gurobi Solver, which employs data supplied by a well‐known e‐commerce firm. We introduce a two‐phase heuristic solution methodology to tackle larger networks’ complexities. This method consists of the clustering phase (K‐means clustering method) and the optimization phase. The robustness of the developed mathematical modeling is demonstrated by testing with varied large problem instances. The evaluation shows that expanding destination options boosts drone demand until saturation, necessitating more drones. Efficient route planning and fleet adjustments are crucial for meeting rising demand and satisfying customers amidst dense clustering. This model helps e‐commerce manage daily last‐mile drone deliveries and anticipate future growth.", "keywords": [ "Drone", "Computer science", "Last mile (transportation)", "Software deployment", "Operations research", "Cluster analysis", "Linear programming", "Solver", "Integer programming", "Mathematical optimization", "Optimization problem", "Heuristic" ], "cited_by_count": 20, "is_retracted": false, "is_paratext": false, "open_access_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/itor.13527" }, { "id": "https://openalex.org/W4295936130", "doi": "10.2139/ssrn.4214918", "title": "Last-mile Delivery in Health Care: Drone Delivery for Blood Products in Rwanda", "year": 2022, "publication_date": "2022-01-01", "type": "preprint", "language": "en", "authors": [ "H. Harriet Jeon", "Claudio Lucarelli", "Jean Baptiste Mazarati", "Donatien Ngabo", "Hummy Song" ], "first_author": "H. Harriet Jeon", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Leapfrogging", "Mile", "Last mile (transportation)", "Business", "Health care delivery", "Health care", "Medical emergency", "Medicine", "Geography", "Economics", "Economic growth" ], "cited_by_count": 11, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.4214918" }, { "id": "https://openalex.org/W4297109112", "doi": "10.1016/j.trc.2022.103901", "title": "Truck–drone hybrid routing problem with time-dependent road travel time", "year": 2022, "publication_date": "2022-09-26", "type": "article", "language": "en", "authors": [ "Yong Wang", "Zheng Wang", "Xiangpei Hu", "Guiqin Xue", "Xiangyang Guan" ], "first_author": "Yong Wang", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Vehicle routing problem", "Routing (electronic design automation)", "Time travel", "Computer science", "Travel time", "Transport engineering", "Automotive engineering", "Engineering", "Computer network", "Artificial intelligence" ], "cited_by_count": 206, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trc.2022.103901" }, { "id": "https://openalex.org/W3128472991", "doi": "10.1002/net.22019", "title": "Parcel delivery cost minimization with time window constraints using trucks and drones", "year": 2021, "publication_date": "2021-02-02", "type": "article", "language": "en", "authors": [ "Marc‐Antoine Coindreau", "Olivier Gallay", "Nicolas Zufferey" ], "first_author": "Marc‐Antoine Coindreau", "venue": "Networks", "publisher": "Wiley", "abstract": "Abstract We propose a model for solving a parcel delivery problem with a fleet of trucks embedded with drones. When appropriate, drones are loaded with a parcel, launched directly from the truck, and sent to a client. Afterward, the drones autonomously return to the truck to be replenished and recharged. Inspired by the case of a large European logistics provider, the proposed modeling framework confronts realistic delivery problems involving time windows, limited drone autonomy, and the eligibility of clients to be served by drones. The considered global cost function includes fixed daily vehicle fares, driver wages, and the fuel and electricity consumption to power trucks and drones. To solve the problems at hand, we propose a mixed‐integer linear programming formulation and an adaptive large neighborhood search. Moreover, we introduce an efficient modeling framework to manage the numerous synchronization constraints induced by the simultaneous use of trucks and drones. We analyze the benefits of this new transportation concept for delivery problems involving up to 100 parcels. Results show that truck‐and‐drone solutions can reduce costs up to 34% compared to traditional truck‐only delivery. From a managerial perspective, we show that a certain percentage of client locations must be reachable by drone to make truck‐and‐drone solutions competitive (i.e., if the fixed costs of the drones are compensated for by the savings on truck routes) and compare the cost structures of truck‐and‐drone versus truck‐only solutions.", "keywords": [ "Drone", "Truck", "Computer science", "Operations research", "Controller (irrigation)", "Minification", "Integer programming", "Transport engineering", "Automotive engineering", "Engineering" ], "cited_by_count": 53, "is_retracted": false, "is_paratext": false, "open_access_url": "https://archive-ouverte.unige.ch/unige:152406" }, { "id": "https://openalex.org/W4391103450", "doi": "10.3390/drones8010027", "title": "Truck-Drone Delivery Optimization Based on Multi-Agent Reinforcement Learning", "year": 2024, "publication_date": "2024-01-20", "type": "article", "language": "en", "authors": [ "Zhiliang Bi", "Xiwang Guo", "Jiacun Wang", "Shujin Qin", "Guanjun Liu" ], "first_author": "Zhiliang Bi", "venue": "Drones", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "In recent years, the adoption of truck–drone collaborative delivery has emerged as an innovative approach to enhance transportation efficiency and minimize the depletion of human resources. Such a model simultaneously addresses the endurance limitations of drones and the time wastage incurred during the “last-mile” deliveries by trucks. Trucks serve not only as a carrier platform for drones but also as storage hubs and energy sources for these unmanned aerial vehicles. Drawing from the distinctive attributes of truck–drone collaborative delivery, this research has created a multi-drone delivery environment utilizing the MPE library. Furthermore, a spectrum of optimization techniques has been employed to enhance the algorithm’s efficacy within the truck–drone distribution system. Finally, a comparative analysis is conducted with other multi-agent reinforcement learning algorithms within the same environment, thus affirming the rationality of the problem formulation and highlighting the algorithm’s superior performance.", "keywords": [ "Drone", "Truck", "Reinforcement learning", "Computer science", "Food delivery", "Transport engineering", "Simulation", "Engineering", "Automotive engineering", "Artificial intelligence", "Business" ], "cited_by_count": 40, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2504-446X/8/1/27/pdf?version=1705903587" }, { "id": "https://openalex.org/W3120782450", "doi": "10.1109/access.2021.3050658", "title": "A New Truck-Drone Routing Problem for Parcel Delivery Services Aided by Parking Lots", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Javier E. Gómez-Lagos", "Alfredo Candia-Véjar", "Flavio Encina" ], "first_author": "Javier E. Gómez-Lagos", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Collaborative routing aided by drones in last-mile delivery (LMD) has been an extensively studied topic in recent years. In this article, a new optimization problem for collaborative routing with a truck and a fleet of drones in LMD is introduced. The problem proposes a new strategy to coordinate a truck and a fleet of drones to serve a given set of customers. The plan is based on identifying the locations where the truck can park and where the drones fly to serve the customers. A procedure to locate these parking lots conveniently is given. For the transportation network, which includes these points, a mixed linear integer programming formulation is provided, which aims to minimize the makespan of serving all the customers. Computational experiments on a set of problem instances were conducted to analyze the model solutions' characteristics and find their computational limits. The experiments showed that the proposed model could significantly improve the results obtained when only the truck delivers. Additionally, we propose a GRASP metaheuristic to solve instances of greater size. Its computational performance was studied when applied to a set of instances with different characteristics. The paper discusses some insights obtained from the computational experimentation and presents future research directions.", "keywords": [ "Truck", "Drone", "Computer science", "Routing (electronic design automation)", "Metaheuristic", "GRASP", "Integer programming", "Vehicle routing problem", "Set (abstract data type)", "Plan (archaeology)", "Job shop scheduling", "Operations research" ], "cited_by_count": 50, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/9312710/09319131.pdf" }, { "id": "https://openalex.org/W4380629997", "doi": "10.3390/en16124656", "title": "Sustainability Aspects of Drone-Assisted Last-Mile Delivery Systems—A Discrete Event Simulation Approach", "year": 2023, "publication_date": "2023-06-12", "type": "article", "language": "en", "authors": [ "Boglárka Eisinger Balassa", "Réka Koteczki", "Bence Lukács", "László Buics" ], "first_author": "Boglárka Eisinger Balassa", "venue": "Energies", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The goal of this article is to examine the advantages and disadvantages of the application of drones in last-mile delivery systems from a sustainability point of view regarding CO2 emissions and energy consumption. As commercial drones are developing rapidly, the application of such tools in the field of last-mile delivery and transportation can offer many opportunities to increase service flexibility, reduce delivery time and decrease CO2 emissions and energy consumption. In this article, a discrete event simulation is applied to examine how the assistance of drones in parcel delivery services can influence the sustainability aspects of such services regarding CO2 emissions and energy consumption in an urban environment. Based on factory parameters, a vehicle-based delivery scenario is compared to a drone-assisted scenario under ideal conditions. According to the results, within the simulation parameters with the assistance of drones, a decrease in CO2 emissions and energy consumption is possible in last-mile delivery services, but more environmental, technological and financial limitations should also be addressed and incorporated to determine whether such a development is worthwhile from a last-mile delivery company’s point of view.", "keywords": [ "Last mile (transportation)", "Drone", "Energy consumption", "Sustainability", "Mile", "Flexibility (engineering)", "Discrete event simulation", "Environmental economics", "Consumption (sociology)", "Transport engineering", "Computer science", "Engineering" ], "cited_by_count": 23, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1996-1073/16/12/4656/pdf?version=1686558953" }, { "id": "https://openalex.org/W4387804330", "doi": "10.1016/j.tranpol.2023.10.002", "title": "The impact of civil airspace policies on the viability of adopting autonomous unmanned aerial vehicles in last-mile applications", "year": 2023, "publication_date": "2023-10-20", "type": "article", "language": "en", "authors": [ "Mo ElSayed", "Ahmed Foda", "Moataz Mohamed" ], "first_author": "Mo ElSayed", "venue": "Transport Policy", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Mile", "Last mile (transportation)", "Range (aeronautics)", "Aeronautics", "Ranging", "Transport engineering", "Drone", "Computer science", "Operations research", "Engineering", "Aerospace engineering", "Telecommunications" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tranpol.2023.10.002" }, { "id": "https://openalex.org/W4403355727", "doi": "10.1080/15568318.2024.2407150", "title": "Last mile delivery with drones: A carbon emissions comparison", "year": 2024, "publication_date": "2024-09-01", "type": "article", "language": "en", "authors": [ "Jay R. Brown", "Maxim A. Bushuev" ], "first_author": "Jay R. Brown", "venue": "International Journal of Sustainable Transportation", "publisher": "Taylor & Francis", "abstract": "The development and potential adoption of drones or unmanned aerial vehicles as delivery vehicles creates incredible opportunities and unique challenges for last mile delivery. This research first presents a last mile delivery fleet model with drones that can be further modified and expanded over time. The model shows the optimal number of drones needed based on deterministic or stochastic demand using both traditional charging and battery swapping. The research then compares the carbon emissions of four delivery modes: traditional internal combustion delivery vehicles, all-electric vehicles, plug-in hybrids, and drones within the context of last mile delivery. Findings reveal that the breakdown of carbon emissions by delivery modality depends on parameter assumptions, ambient temperature, delivery radius, electric grid pollution rate, and number of customers.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "Environmental science", "Greenhouse gas", "Business", "Environmental planning", "Environmental engineering", "Geography" ], "cited_by_count": 13, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1080/15568318.2024.2407150" }, { "id": "https://openalex.org/W4392999284", "doi": "10.1111/itor.13452", "title": "Traveling salesman problem with drone and bicycle: multimodal last‐mile e‐mobility", "year": 2024, "publication_date": "2024-03-20", "type": "article", "language": "en", "authors": [ "Erfan Babaee Tırkolaee", "Emre Çakmak", "Saliha Karadayi‐Usta" ], "first_author": "Erfan Babaee Tırkolaee", "venue": "International Transactions in Operational Research", "publisher": "Wiley", "abstract": "Abstract Recently, the multimodal last‐mile e‐mobility concept has been at the center of attention for cleaner, greener, and more accessible urban deliveries. As part of sustainable transportation systems, multimodal e‐mobility is proper for a variety of logistics operations as well as medical applications. This work tries to address a novel application of multimodal e‐mobility through introducing and modeling the traveling salesman problem with drone and bicycle (TSP‐D‐B). Therefore, a novel mixed integer linear programming model is developed to formulate the problem wherein the total traveling time is minimized. As part of the last‐mile delivery, a fleet of three vehicles including a truck, a drone, and a bicycle is taken into account to serve the customers in a single visit. The truck is considered as the main vehicle, while the drone and bicycle can be preferred in case of emergencies such as traffic or route failures. In order to assess the complexity, validity and applicability of the offered model, a dataset including 64 different benchmarks is generated, and according to the findings, the model is able to efficiently solve the benchmarks for up to 50 customers in 685 s maximum. A comparison is also made between TSP‐D‐B, the classic version of the TSP and the TSP‐D, which reveals that TSP‐D‐B provides appropriate service time savings in all benchmarks. Finally, another comparative analysis is made using several instances adapted from the literature. It is revealed that TSP‐D‐B leads to significant time savings in most instances.", "keywords": [ "Drone", "Travelling salesman problem", "Mile", "Computer science", "Geography", "Biology", "Algorithm", "Botany" ], "cited_by_count": 20, "is_retracted": false, "is_paratext": false, "open_access_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/itor.13452" }, { "id": "https://openalex.org/W4225772876", "doi": "10.1007/s00500-022-07094-9", "title": "Last-mile drone delivery combinatorial double auction model using multi-objective evolutionary algorithms", "year": 2022, "publication_date": "2022-04-12", "type": "article", "language": "en", "authors": [ "Chen-Wei Lee", "Wai-Peng Wong" ], "first_author": "Chen-Wei Lee", "venue": "Soft Computing", "publisher": "Springer Science+Business Media", "abstract": "Abstract This study proposes a combinatorial double auction bi-objective winner determination problem for last-mile delivery using drone. Prior studies are limited on solving mixed integer model, which are not efficient for large-scale scenario. However, this is not practical in real cases as the computation time to obtain the solution is longer due to number of combinations of packages and participants anticipated in the last-mile delivery platform. Four multi-objective evolutionary algorithms (MOEAs) with the decomposed winner determination problem model are experimented. This study is able to yield Pareto optimal solutions from multiple runs of mixed linear integer programming (MILP) using different objectives weights in the model. Unmanned aerial vehicle, or drone, has potential to reduce cost and save time for last-mile logistic operations. The result positively shows MOEAs are more efficient than MILP in yielding a set of feasible solutions for undertaking complex winner determination problem models. The percentage of improvement in terms of time spent identifying the best option is almost 100%. This is likely an unprecedented research in drone where combinatorial double auction is applied to complex drone delivery services and MOEAs are used to solve the associated winner determination problem model.", "keywords": [ "Drone", "Computer science", "Mathematical optimization", "Integer programming", "Last mile (transportation)", "Combinatorial auction", "Integer (computer science)", "Pareto principle", "Set (abstract data type)", "Linear programming", "Evolutionary algorithm", "Multi-objective optimization" ], "cited_by_count": 13, "is_retracted": false, "is_paratext": false, "open_access_url": "https://link.springer.com/content/pdf/10.1007/s00500-022-07094-9.pdf" }, { "id": "https://openalex.org/W4398793435", "doi": "10.1016/j.tre.2024.103573", "title": "The multi-fleet delivery problem combined with trucks, tricycles, and drones for last-mile logistics efficiency requirements under multiple budget constraints", "year": 2024, "publication_date": "2024-05-24", "type": "article", "language": "en", "authors": [ "Enming Chen", "Zhongbao Zhou", "Ruiyang Li", "Zhongxiang Chang", "Jianmai Shi" ], "first_author": "Enming Chen", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Truck", "Mile", "Last mile (transportation)", "Transport engineering", "Drone", "Operations management", "Business", "Environmental science", "Operations research", "Engineering", "Automotive engineering", "Geography" ], "cited_by_count": 35, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2024.103573" }, { "id": "https://openalex.org/W4389417919", "doi": "10.1016/j.tre.2023.103377", "title": "Optimization of the drone-assisted pickup and delivery problem", "year": 2023, "publication_date": "2023-12-06", "type": "article", "language": "en", "authors": [ "Timothy Mulumba", "Ali H. Diabat" ], "first_author": "Timothy Mulumba", "venue": "Transportation Research Part E Logistics and Transportation Review", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Pickup", "Context (archaeology)", "Computer science", "Heuristic", "Bottleneck", "Operations research", "Last mile (transportation)", "Simulation", "Engineering", "Automotive engineering" ], "cited_by_count": 88, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tre.2023.103377" }, { "id": "https://openalex.org/W4322707283", "doi": "10.1109/access.2023.3247501", "title": "Energy Efficient UAV-Based Last-Mile Delivery: A Tactical-Operational Model With Shared Depots and Non-Linear Energy Consumption", "year": 2023, "publication_date": "2023-01-01", "type": "article", "language": "en", "authors": [ "Maria Elena Bruni", "Sara Khodaparasti", "Guido Perboli" ], "first_author": "Maria Elena Bruni", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "This paper studies the drone-aided last-mile delivery problem with shared depot resources. Our research motivation comes from E-commerce logistics, where big companies such as Amazon, are already filing up patents for the development of drone-friendly fulfillment centers towers that could serve as both charging hubs and convenient pit stops for delivery drones to pick up and drop off packages efficiently. We mainly focus on the tactical decisions about the selection of shared fulfillment centers used as the drone launch and retrieve stations and the fleet size plans. The operational drone route decisions are also incorporated into a unified framework to account for the mutual impact between tactical and operational plans. Moreover, we consider explicitly the non-linear and load-dependent nature of the energy consumption function for drone batteries. The problem is formulated as a mixed integer program with linear constraints, developed in the realm of layered networks, where the non-linear nature of energy consumption and its load dependency are incorporated and efficiently handled without the need of approximating non-linear terms. The proposed model is tested on an extensive set of instances with up to 75 customers, showing its computational efficiency. Insights about the route costs and spatial configuration of depots are also discussed.", "keywords": [ "Drone", "Computer science", "Energy consumption", "Last mile (transportation)", "Linear programming", "Operations research", "Efficient energy use", "Mile", "Engineering" ], "cited_by_count": 45, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/10005208/10049551.pdf" }, { "id": "https://openalex.org/W2761989652", "doi": "10.1109/mcom.2017.1700239", "title": "Combining Software-Defined and Delay-Tolerant Approaches in Last-Mile Tactical Edge Networking", "year": 2017, "publication_date": "2017-10-01", "type": "article", "language": "en", "authors": [ "Iulisloi Zacarias", "Luciano Paschoal Gaspary", "Andersonn Kohl", "Ricardo Q. A. Fernandes", "Jorgito Matiuzzi Stocchero", "Edison Pignaton de Freitas" ], "first_author": "Iulisloi Zacarias", "venue": "IEEE Communications Magazine", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Network-centric warfare is a no-way-back trend in modern military operations. The application of this concept ranges from upper-level decision making echelons to troop guidance on the battlefield, and many studies have been carried out in this area. However, most of these are concerned with either the higher-level strategic networks, that is, the networks linking the higher echelons with abundant resources, satellite communications, or even a whole network infrastructure, or high-end TEN, representing resource-rich troops in the field, with military aircraft, battleships, or ground vehicles equipped with powerful wireless communication devices and (almost) unrestricted energy resources for communication. However, these studies fail to take into account the \"last-mile TEN,\" which comprises resource constrained communication devices carried by troopers, equipping sensor nodes deployed in the field or small unmanned aerial vehicles. In an attempt to fill this gap in the studies on battlefield networking, this article seeks to combine software-defined and delay-tolerant approaches to support the diverse range of strict requirements for applications in the last-mile TEN.", "keywords": [ "Computer science", "Mile", "Last mile (transportation)", "Battlefield", "Telecommunications", "Resource (disambiguation)", "Software", "Wireless sensor network", "Wireless", "Wireless network", "Field (mathematics)", "Computer security" ], "cited_by_count": 50, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/mcom.2017.1700239" }, { "id": "https://openalex.org/W3045631220", "doi": "10.1109/tii.2020.3012162", "title": "Drone Routing in a Time-Dependent Network: Toward Low-Cost and Large-Range Parcel Delivery", "year": 2020, "publication_date": "2020-07-28", "type": "article", "language": "en", "authors": [ "Hailong Huang", "Andrey V. Savkin", "Chao Huang" ], "first_author": "Hailong Huang", "venue": "IEEE Transactions on Industrial Informatics", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Drones are a promising tool for parcel delivery, since they are cost-efficient and environmentally friendly. However, owing to the limited capacity of the on-board battery, their flight range is constrained. Thus, they cannot deliver some parcels if the customers are too far from the depot. To address this issue, this article proposes a novel method, in which a parcel delivery drone can “take” a public transportation vehicle and travel on its roof. The problem under consideration is how to make use of the public transportation network to route the drone between the depot and the customer. Compared to the currently available methods that use drones, the most important merit of this approach is a significant expansion of the delivery area. We construct a multimodal network consisting of public transportation vehicles' trips and drone flights. Because of the complexity of this multimodal network, we convert it to a simple network with a set of simple procedures. In the extended network, we formulate the shortest drone path problem that minimizes the return instant to the depot, subject to that the drone energy consumption on this path is no greater than the initial energy. We present a Dijkstra-based method to find the shortest drone path. Moreover, we extend the proposed method to the case with uncertainty, because the public transportation vehicles cannot exactly follow their timetables in practice. Simulation results are presented to demonstrate how the method works.", "keywords": [ "Drone", "Computer science", "Shortest path problem", "Dijkstra's algorithm", "Routing (electronic design automation)", "Energy consumption", "Transport engineering", "Operations research", "TRIPS architecture", "Path (computing)", "Engineering", "Computer network" ], "cited_by_count": 59, "is_retracted": false, "is_paratext": false, "open_access_url": "https://unsworks.unsw.edu.au/bitstreams/09409853-7f0c-4c42-9c08-04e9e7384d15/download" }, { "id": "https://openalex.org/W4318141875", "doi": "10.1109/maes.2023.3240112", "title": "A Cyber-Physical System's Roadmap to Last-Mile Delivery Drones", "year": 2023, "publication_date": "2023-01-26", "type": "article", "language": "en", "authors": [ "Bruno S. Faiçal", "Cesar Augusto Cavalheiro Marcondes", "Denis Silva Loubach", "Elton Felipe Sbruzzi", "Filipe Alves Neto Verri", "Johnny Marques", "Lourenço Alves Pereira", "Marcos R. O. A. Máximo", "Vitor Curtis" ], "first_author": "Bruno S. Faiçal", "venue": "IEEE Aerospace and Electronic Systems Magazine", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "According to recent studies, unmanned aerial vehicles can play a game-changing part in cost reduction and speed increase to address the last-mile delivery problem and attend to emergencies. Last-mile delivery services are becoming more and more relevant, especially when in times when social distance is required. However, a systemic view of how to provide a feasible solution to enable this application as a vertical market in the urban context is still inexistent. Given this scenario, this article contributes by proposing a cyber-physical system roadmap applicable to last-mile delivery drones. The proposed cyber-physical system (CPS) guidelines are based on a system's ability to enhance an operation toward smart cities’ governance. This article also discusses topics from air–space control and reservation to communication infrastructure and decentralized control supported on a blockchain.", "keywords": [ "Drone", "Last mile (transportation)", "Mile", "Cyber-physical system", "Context (archaeology)", "Reservation", "Computer security", "Computer science", "Resilience (materials science)", "Telecommunications", "Engineering", "Computer network" ], "cited_by_count": 14, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/maes.2023.3240112" }, { "id": "https://openalex.org/W3083698083", "doi": "10.1109/isc251055.2020.9239082", "title": "Multimodal Autonomous Last-Mile Delivery System Design and Application", "year": 2020, "publication_date": "2020-09-28", "type": "conference-paper", "language": "en", "authors": [ "Farah Samouh", "Veronica Gluza", "Shadi Djavadian", "Seyed Mehdi Meshkani", "Bilal Farooq" ], "first_author": "Farah Samouh", "venue": null, "publisher": null, "abstract": "With the rapid increase in congestion, alternative solutions are needed to efficiently use the capacity of our existing networks. This paper focuses on exploring the emerging autonomous technologies for on-demand food delivery in congested urban cities. Three different last mile food delivery systems are proposed in this study employing aerial and ground autonomous vehicles technologies. The three proposed systems are: robot delivery system, drone delivery system and a hybrid delivery system. In the hybrid system the concept of hub-and-spoke network is explored in order to consolidate orders and reach more destinations in less time. To investigate the performance of the three proposed delivery systems, they are applied to the city of Mississauga network, in an in-house agent-based simulation in MATLAB. 18 Scenarios are tested differing in terms of demand and fleet size. The results show that the hybrid robot-drone delivery system performs the best with a fleet side of 25 robots and 15 drones and with an average preparation and delivery time less than the individual robot and drone system by 48 % and 42% respectively.", "keywords": [ "Drone", "Food delivery", "Last mile (transportation)", "Hybrid system", "Computer science", "Delivery system", "Robot", "Mile", "Real-time computing", "Simulation", "Transport engineering", "Engineering" ], "cited_by_count": 32, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2009.01960" }, { "id": "https://openalex.org/W1073972851", "doi": "10.2139/ssrn.2639672", "title": "Optimization Approaches for the Traveling Salesman Problem with Drone", "year": 2015, "publication_date": "2015-01-01", "type": "preprint", "language": "en", "authors": [ "Niels A.H. Agatz", "Paul Bouman", "Marie Evans Schmidt" ], "first_author": "Niels A.H. Agatz", "venue": "SSRN Electronic Journal", "publisher": "RELX Group (Netherlands)", "abstract": null, "keywords": [ "Travelling salesman problem", "Drone", "2-opt", "Bottleneck traveling salesman problem", "Computer science", "Lin–Kernighan heuristic", "Traveling purchaser problem", "Combinatorial optimization", "Mathematical optimization", "Mathematics", "Biology", "Algorithm" ], "cited_by_count": 105, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.2139/ssrn.2639672" }, { "id": "https://openalex.org/W3094316289", "doi": "10.1109/access.2020.3030612", "title": "An Analysis on Tradable Permit Models for Last-Mile Delivery Drones", "year": 2020, "publication_date": "2020-01-01", "type": "article", "language": "en", "authors": [ "Filipe Alves Neto Verri", "Cesar Augusto Cavalheiro Marcondes", "Denis Silva Loubach", "Elton Felipe Sbruzzi", "Johnny Marques", "Lourenço Alves Pereira", "Marcos R. O. A. Máximo", "Vitor Curtis" ], "first_author": "Filipe Alves Neto Verri", "venue": "IEEE Access", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "Drones can play a game-changing role in reducing both cost and time in the context of last-mile deliveries. This paper addresses the last-mile delivery problem from a complex system viewpoint, where the collective performance of the drones is investigated. We consider a last-mile delivery system with a tradable permit model (TPM) for airspace use. Typically, in other research works regarding last-mile delivery drones, a fully cooperative centralized scenario is contemplated. In our approach, due to the TPM, the agents (i.e. drones) need to compete for airspace permits in a distributed manner. We simulate the system and evaluate how different parameters, such as the arrival rate and airspace dimensions, impact the system behavior in terms of the cost and time needed by the drones to acquire flight permits, and the airspace utilization. We use a simplified simulation model, where the agents' strategies are naïve, and the drones' flight dynamics are not accounted for. Nevertheless, the simulation's level of detail is adequate for capturing interesting properties from the agents' collective behavior, as our results support. The obtained results show that the system's performance is satisfactory, even with naïve agents and under high traffic conditions. Moreover, a real-world implementation of our competitive decentralized approach would lead to advantages, such as fast permit transactions, simple computational infrastructures, and error resilience.", "keywords": [ "Drone", "Mile", "Computer science", "Last mile (transportation)", "Context (archaeology)", "Resilience (materials science)", "Air traffic control", "Operations research", "Simulation", "Aeronautics", "Computer security", "Engineering" ], "cited_by_count": 15, "is_retracted": false, "is_paratext": false, "open_access_url": "https://ieeexplore.ieee.org/ielx7/6287639/8948470/09222133.pdf" }, { "id": "https://openalex.org/W3119780768", "doi": "10.3390/ijerph18020682", "title": "A Psychoacoustic Approach to Building Knowledge about Human Response to Noise of Unmanned Aerial Vehicles", "year": 2021, "publication_date": "2021-01-14", "type": "article", "language": "en", "authors": [ "Antonio J. Torija", "Charlotte Clark" ], "first_author": "Antonio J. Torija", "venue": "International Journal of Environmental Research and Public Health", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "We are on the cusp of a revolution in the aviation sector, driven by the significant progress in electric power and battery technologies, and autonomous systems. Several industry leaders and governmental agencies are currently investigating the use of Unmanned Aerial Vehicles (UAVs), or \"drones\" as commonly known, for an ever-growing number of applications-from blue light services to parcel delivery and urban mobility. Undoubtedly, the operation of UAVs will lead to noise exposure, which has the potential to become a significant public health issue. This paper first describes the main acoustic and operational characteristics of UAVs, as an unconventional noise source compared to conventional civil aircraft. Gaps in the literature and the regulations on the noise metrics and acceptable noise levels are identified and discussed. The state-of-the-art evidence on human response to aircraft and other environmental noise sources is reviewed and its application for UAVs discussed. A methodological framework is proposed for building psychoacoustic knowledge, to inform systems and operations development to limit the noise impact on communities.", "keywords": [ "Drone", "Psychoacoustics", "Noise (video)", "Aviation", "Noise control", "Computer science", "Soundscape", "Aircraft noise", "Noise pollution", "Aeronautics", "Telecommunications", "Engineering" ], "cited_by_count": 88, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1660-4601/18/2/682/pdf?version=1610686743" }, { "id": "https://openalex.org/W3181767153", "doi": "10.3390/app11146443", "title": "Optimization of Truck-Drone Parcel Delivery Using Metaheuristics", "year": 2021, "publication_date": "2021-07-13", "type": "article", "language": "en", "authors": [ "Sarab AlMuhaideb", "Taghreed Alhussan", "Sara Alamri", "Yara Altwaijry", "Lujain Aljarbou", "Haifa Alrayes" ], "first_author": "Sarab AlMuhaideb", "venue": "Applied Sciences", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "This research addresses a variant of the traveling salesman problem in drone-based delivery systems known as the TSP-D. The TSP-D is a combinatorial optimization problem in which a truck and a drone collaborate to deliver parcels to customers, with the objective of minimizing the total delivery time. Determining the optimal solution is NP-hard; thus, the size of the problems that can be solved optimally is limited. Therefore, metaheuristics are used to solve the problem. Metaheuristics are adaptive and intelligent algorithms that have proved their success in many similar problems. In this study, a solution to the TSP-D problem using the greedy, randomized adaptive search procedure with two local search alternatives and a self-adaptive neighborhood selection scheme is presented. The proposed approach was tested on 200 instances with different properties from the publicly available “Instances of TSP with Drone” benchmark. Results were evaluated against state-of-the-art algorithms. Non-parametric statistical tests concluded that the proposed approach has comparable performance to the rival algorithms (p=0.074) in terms of tour duration. The proposed approach has better or similar performance in instances where the drone and truck have the same speed (α=1).", "keywords": [ "Drone", "Metaheuristic", "Travelling salesman problem", "Mathematical optimization", "Computer science", "Benchmark (surveying)", "Truck", "Local search (optimization)", "Combinatorial optimization", "Parametric statistics", "Mathematics", "Engineering" ], "cited_by_count": 35, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2076-3417/11/14/6443/pdf?version=1626160301" }, { "id": "https://openalex.org/W4387539248", "doi": "10.3390/systems11100509", "title": "Evolution, Challenges, and Opportunities of Transportation Methods in the Last-Mile Delivery Process", "year": 2023, "publication_date": "2023-10-11", "type": "article", "language": "en", "authors": [ "Xiaonan Zhu", "Lanhui Cai", "Po‐Lin Lai", "Xueqin Wang", "Fei Ma" ], "first_author": "Xiaonan Zhu", "venue": "Systems", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The rapid development of modern logistics and e-commerce highlights the importance of exploring various modes of transportation in the last-mile delivery (LMD) process. However, no comprehensive studies exist in the literature exploring all modes of LMD transportation, the changes in these transportation modes, and the commonalities between them. In this study, we address this gap by conducting a systematic review of 150 academic journal articles utilizing a combination of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) content analysis and text mining analysis. Nine primary transportation methods (parcel lockers, autonomous drones, trucks, bicycles, crowd logistics, electric vehicles, tricycles, autonomous robots, and autonomous vehicles) are identified in this research. Additionally, we provide an analysis of the historical changes in these transportation modes in LMD. Using a bottom-up induction method, we identify the three major clusters of scholarly focus in the LMD literature: emphasis on value co-creation between consumers and logistics providers, practical delivery performance (path optimization or algorithms), and environmental friendliness. Further, we analyze the main themes under each cluster, leading to the identification of opportunities, challenges, and future research agendas. Our findings have implications for scholars, policymakers, and other stakeholders involved in LMD transportation modes.", "keywords": [ "Truck", "Last mile (transportation)", "Process (computing)", "Identification (biology)", "City logistics", "Drone", "Business", "Transport engineering", "Supply chain", "Computer science", "Mile", "Marketing" ], "cited_by_count": 41, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2079-8954/11/10/509/pdf?version=1696997115" }, { "id": "https://openalex.org/W4210344377", "doi": "10.1016/j.aei.2022.101536", "title": "Solving the vehicle routing problem with drone for delivery services using an ant colony optimization algorithm", "year": 2022, "publication_date": "2022-01-01", "type": "article", "language": "en", "authors": [ "Shan-Huen Huang", "Ying‐Hua Huang", "Carola Alejandra Blazquez", "Chia-Yi Chen" ], "first_author": "Shan-Huen Huang", "venue": "Advanced Engineering Informatics", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Truck", "Ant colony optimization algorithms", "Vehicle routing problem", "Computer science", "Routing (electronic design automation)", "Service (business)", "Integer programming", "Ant colony", "Operations research", "Engineering", "Mathematical optimization" ], "cited_by_count": 175, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.aei.2022.101536" }, { "id": "https://openalex.org/W4385748676", "doi": "10.1016/j.rtbm.2023.101029", "title": "Technical and legal critical success factors: Feasibility of drones & AGV in the last-mile-delivery", "year": 2023, "publication_date": "2023-08-10", "type": "article", "language": "en", "authors": [ "Christian Fehling", "Adriana Saraceni" ], "first_author": "Christian Fehling", "venue": "Research in Transportation Business & Management", "publisher": "Elsevier BV", "abstract": "This paper aims to provide a current status of the legal situation necessary due to the regular changes of the law of the EU and Germany, by identify technical and legal critical success factors of the feasibility of drones and AGVs in last-mile-delivery. Furthermore, the paper provides importance rankings for legal and technical critical success factors from the point of view of logistics and supply chain experts. A conceptual model was developed capturing main legal and technical critical success factors from literature finding and then providing basis to a survey-based study that have been captured online. Results from the survey were evaluated and compared against each other using the Analytical Hierarchy Process. The results are based on business-to-business relationships between logistics service and mobility providers, as well as technical developers. The results of this research can help managers of large providers, transport companies in general and governments as well as political decision-makers in the innovation field to understand the legal situation of the EU and Germany as well as the technical problems that have to be overcome to profit from future technology in the last-mile-delivery.", "keywords": [ "Drone", "Critical success factor", "Business", "Last mile (transportation)", "Profit (economics)", "Service provider", "Mile", "Process management", "Marketing", "Service (business)" ], "cited_by_count": 20, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.rtbm.2023.101029" }, { "id": "https://openalex.org/W3180196087", "doi": "10.1016/j.trc.2021.103280", "title": "Exact methods for the traveling salesman problem with multiple drones", "year": 2021, "publication_date": "2021-07-09", "type": "article", "language": "en", "authors": [ "Sara Cavani", "Manuel Iori", "Roberto Roberti" ], "first_author": "Sara Cavani", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": "Drone delivery is drawing increasing attention in last-mile delivery. Effective solution methods to solve decision-making problems arising in drone delivery allow to run and assess drone delivery systems. In this paper, we focus on delivery systems with a single traditional vehicle and multiple drones working in tandem to fulfill customer requests. We address the Traveling Salesman Problem with Multiple Drones (TSP-MD) and investigate the modeling challenges posed by the presence of multiple drones, which have proven to be hard to handle in the literature. We propose a compact Mixed-Integer Linear Programming (MILP) model to formulate the TSP-MD and several families of valid inequalities. Moreover, we illustrate an exact decomposition approach based on the compact MILP and a branch-and-cut algorithm. We show that this exact approach can solve instances with up to 24 customers to proven optimality, improving upon existing exact methods that can solve similar problems with up to ten customers only.", "keywords": [ "Drone", "Travelling salesman problem", "Computer science", "Mathematical optimization", "Integer programming", "Linear programming", "Mathematics", "Algorithm" ], "cited_by_count": 100, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S0968090X21002928/pdf" }, { "id": "https://openalex.org/W4391944067", "doi": "10.1016/j.eswa.2024.123472", "title": "Ensemble multi-objective optimization approach for heterogeneous drone delivery problem", "year": 2024, "publication_date": "2024-02-19", "type": "article", "language": "en", "authors": [ "Xupeng Wen", "Guohua Wu", "Shuanglin Li", "Ling Wang" ], "first_author": "Xupeng Wen", "venue": "Expert Systems with Applications", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Computer science", "Crossover", "Pareto principle", "Heuristic", "Cluster analysis", "Genetic algorithm", "Multi-objective optimization", "Payload (computing)", "Benchmark (surveying)", "Mathematical optimization", "Machine learning" ], "cited_by_count": 34, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.eswa.2024.123472" }, { "id": "https://openalex.org/W4385348396", "doi": "10.3390/su151511588", "title": "Leveraging Drone Technology for Last-Mile Deliveries in the e-Tailing Ecosystem", "year": 2023, "publication_date": "2023-07-27", "type": "article", "language": "en", "authors": [ "Hokey Min" ], "first_author": "Hokey Min", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The extended lockdown and limited in-person interactions resulting from the COVID-19 pandemic have radically changed many consumers’ shopping behavior. These changes include a rapid rise in online shopping, leading to the fast growth of e-logistics. As the popularity of e-logistics has spread worldwide, many retailers’ success hinges on their ability to deliver products to their consumers’ doorsteps. This ability cannot be nurtured without handling last-mile delivery services in a cost-efficient and sustainable way. However, last-mile delivery services pose unique and complex challenges since they require individual, door-to-door services that limit the opportunity to consolidate small shipments into large ones and thus increase cost burdens for retailers selling products online. These challenges call for new, innovative ways of managing last-mile delivery services. Such practices include utilizing emerging drone technology that allows retailers to deliver products from point to point ubiquitously without a pilot, driver, or vehicle consuming too much fossil fuel. This paper is one of the first studies to develop viable strategic plans for commercializing drone technology in the e-tailing ecosystem using visual decision-aid tools and performance management systems.", "keywords": [ "Drone", "Last mile (transportation)", "Popularity", "Mile", "Business", "Best practice", "Marketing", "Geography" ], "cited_by_count": 16, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/15/15/11588/pdf?version=1690438337" }, { "id": "https://openalex.org/W4413513450", "doi": "10.1016/j.cie.2025.111477", "title": "A literature review of collaborative truck and drone in last-mile delivery", "year": 2025, "publication_date": "2025-08-25", "type": "article", "language": "en", "authors": [ "Milad Faramarzzadeh", "Şener Akpınar" ], "first_author": "Milad Faramarzzadeh", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Truck", "Aeronautics", "Engineering", "Transport engineering", "Geography", "Aerospace engineering", "Geodesy", "Biology" ], "cited_by_count": 13, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2025.111477" }, { "id": "https://openalex.org/W3014427406", "doi": "10.3390/s20072045", "title": "Scheduling of a Parcel Delivery System Consisting of an Aerial Drone Interacting with Public Transportation Vehicles", "year": 2020, "publication_date": "2020-04-05", "type": "article", "language": "en", "authors": [ "Hailong Huang", "Andrey V. Savkin", "Chao Huang" ], "first_author": "Hailong Huang", "venue": "Sensors", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "This paper proposes a novel parcel delivery system which consists of a drone and public transportation vehicles such as trains, trams, etc. This system involves two delivery schemes: drone-direct scheme referring to delivering to a customer by a drone directly and drone-vehicle collaborating scheme referring to delivering a customer based on the collaboration of a drone and public transportation vehicles. The fundamental characteristics including the delivery time, energy consumption and battery recharging are modelled, based on which a time-dependent scheduling problem for a single drone is formulated. It is shown to be NP-complete and a dynamic programming-based exact algorithm is presented. Since its computational complexity is exponential with respect to the number of customers, a sub-optimal algorithm is further developed. This algorithm accounts the time for delivery and recharging, and it first schedules the customer which leads to the earliest return. Its computational complexity is also discussed. Moreover, extensive computer simulations are conducted to demonstrate the scheduling performance of the proposed algorithms and the impacts of several key system parameters are investigated.", "keywords": [ "Drone", "Scheduling (production processes)", "Public transport", "Transport engineering", "Computer science", "Engineering", "Aeronautics", "Operations management", "Biology" ], "cited_by_count": 49, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1424-8220/20/7/2045/pdf?version=1586758152" }, { "id": "https://openalex.org/W2947430481", "doi": "10.1016/j.tele.2019.05.007", "title": "Segmenting the public’s risk beliefs about drone delivery: A belief system approach", "year": 2019, "publication_date": "2019-05-30", "type": "article", "language": "en", "authors": [ "Xun Zhu" ], "first_author": "Xun Zhu", "venue": "Telematics and Informatics", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Market segmentation", "Marketing", "Demographics", "Population", "Psychology", "Risk perception", "Expectancy theory", "Cognition", "Segmentation", "Personality", "Risk communication" ], "cited_by_count": 42, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.tele.2019.05.007" }, { "id": "https://openalex.org/W2898015416", "doi": null, "title": "The traveling salesman problem with multiple drones : an optimization model for last-mile delivery", "year": 2018, "publication_date": "2018-01-01", "type": "dissertation", "language": "en", "authors": [ "Justin J Yoon" ], "first_author": "Justin J Yoon", "venue": "DSpace@MIT (Massachusetts Institute of Technology)", "publisher": "Massachusetts Institute of Technology", "abstract": "Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018.", "keywords": [ "Travelling salesman problem", "Drone", "Mile", "2-opt", "Last mile (transportation)", "Computer science", "Operations research", "Engineering", "Mathematical optimization", "Geography", "Mathematics", "Algorithm" ], "cited_by_count": 17, "is_retracted": false, "is_paratext": false, "open_access_url": "http://hdl.handle.net/1721.1/117930" }, { "id": "https://openalex.org/W4406168354", "doi": "10.1016/j.scs.2025.106134", "title": "Beyond the last-mile: Environmental and economic assessment of the upcoming drone takeaway delivery system", "year": 2025, "publication_date": "2025-01-08", "type": "article", "language": "en", "authors": [ "Zhi Li", "Siqi Zhou", "Bohan Wang", "Tingxi Zhang", "Shuang Guo" ], "first_author": "Zhi Li", "venue": "Sustainable Cities and Society", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Engineering", "Architectural engineering", "Aeronautics", "Civil engineering", "Transport engineering", "Geography" ], "cited_by_count": 17, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.scs.2025.106134" }, { "id": "https://openalex.org/W4318464221", "doi": "10.3390/s23031463", "title": "Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security", "year": 2023, "publication_date": "2023-01-28", "type": "article", "language": "en", "authors": [ "Asif Mahmud Raivi", "S. M. Asiful Huda", "Muhammad Morshed Alam", "Sangman Moh" ], "first_author": "Asif Mahmud Raivi", "venue": "Sensors", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Recently, owing to the high mobility and low cost of drones, drone-based delivery systems have shown considerable potential for ensuring flexible and reliable parcel delivery. Several crucial design issues must be considered to design such systems, including route planning, payload weight consideration, distance measurement, and customer location. In this paper, we present a survey of emerging drone routing algorithms for drone-based delivery systems, emphasizing three major drone routing aspects: trajectory planning, charging, and security. We focus on practical design considerations to ensure efficient, flexible, and reliable parcel delivery. We first discuss the potential issues arising when designing such systems. Next, we present a novel taxonomy based on the above-mentioned three aspects. We extensively review each algorithm for drone routing in terms of key features and operational characteristics. Furthermore, we compare the algorithms in terms of their main idea, advantages, limitations, and performance aspects. Finally, we present open research challenges to motivate further research in this field. In particular, we focus on the major aspects that researchers and engineers need to consider in order to design effective and reliable drone routing algorithms for drone-based delivery systems.", "keywords": [ "Drone", "Payload (computing)", "Computer science", "Routing (electronic design automation)", "Key (lock)", "Focus (optics)", "Systems engineering", "Risk analysis (engineering)", "Computer security", "Engineering", "Computer network" ], "cited_by_count": 84, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/1424-8220/23/3/1463/pdf?version=1674896807" }, { "id": "https://openalex.org/W3094029732", "doi": "10.1109/icite50838.2020.9231399", "title": "A Method for “Last mile” Distribution Demand for Drones", "year": 2020, "publication_date": "2020-09-01", "type": "conference-paper", "language": "en", "authors": [ "Fang Zhang", "Zhang Hong-Hai" ], "first_author": "Fang Zhang", "venue": "2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)", "publisher": null, "abstract": "To solve the problem of drone demand for “last mile” distribution, many factors such as drone performance, airspace environment and transportation tasks are considered. The objective function is to minimize transportation cost with a UAV demand model. Dynamic allocation algorithm can calculate the optimal demand on the drone. The actual delivery data and low-altitude flight conditions in a certain area are analyzed as examples. The results show that the optimal load of drones is 20kg under the initial parameters, and the optimal loads of drones are 20kg and 25kg when use different drones to delivery together. The method proposed in this paper can not only calculate the demand on unmanned aerial vehicles in this area within milliseconds, but also provide flexible demand schemes when styles of drones, the airspace open-door policies and the transportation demand vary.", "keywords": [ "Drone", "Computer science", "Mile", "Last mile (transportation)", "On demand", "Real-time computing", "Geography" ], "cited_by_count": 9, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/icite50838.2020.9231399" }, { "id": "https://openalex.org/W3004984167", "doi": "10.1109/tvt.2021.3090992", "title": "Shipper Cooperation in Stochastic Drone Delivery: A Dynamic Bayesian Game Approach", "year": 2021, "publication_date": "2021-06-22", "type": "article", "language": "en", "authors": [ "Suttinee Sawadsitang", "Dusit Tao Niyato", "Tan Puay Siew", "Ping Wang", "Sarana Y. Nutanong" ], "first_author": "Suttinee Sawadsitang", "venue": "IEEE Transactions on Vehicular Technology", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "With the recent technological innovation, unmanned aerial vehicles, known as drones, have found numerous applications including package and parcel delivery for shippers. Drone delivery offers benefits over conventional ground-based vehicle delivery in terms of faster speed, lower cost, more environment-friendly, and less manpower needed. However, most of existing studies on drone delivery planning and scheduling focus on a single shipper and ignore uncertainty factors. As such, in this paper, we consider a scenario that multiple shippers can cooperate to minimize their drone delivery cost. We propose the Bayesian Shipper Cooperation in Stochastic Drone Delivery (BCoSDD) framework. The framework is composed of three functions, i.e., package assignment, shipper cooperation formation and cost management. The uncertainties of drone breakdown and misbehavior of cooperative shippers are taken into account by using multistage stochastic programming optimization and dynamic Bayesian coalition formation game. We conduct extensive performance evaluation of the BCoSDD framework by using customer locations from Solomon benchmark suite and a real Singapore logistics industry. As a result, the framework can help the shippers plan and schedule their drone delivery effectively.", "keywords": [ "Drone", "Operations research", "Computer science", "Benchmark (surveying)", "Scheduling (production processes)", "Schedule", "Stochastic programming", "Engineering", "Mathematical optimization", "Operations management" ], "cited_by_count": 35, "is_retracted": false, "is_paratext": false, "open_access_url": "https://arxiv.org/pdf/2002.03118" }, { "id": "https://openalex.org/W4406269539", "doi": "10.1016/j.eswa.2025.126434", "title": "A multi-objective approach for the integrated planning of drone and robot assisted truck operations in last-mile delivery", "year": 2025, "publication_date": "2025-01-10", "type": "article", "language": "en", "authors": [ "Ali Mokhtari Moghadam", "Abdellah Salhi", "Xinan Yang", "Trung Thành Nguyễn", "Pourya Pourhejazy" ], "first_author": "Ali Mokhtari Moghadam", "venue": "Expert Systems with Applications", "publisher": "Elsevier BV", "abstract": "Supply chains are experiencing a major transition driven by changing customer expectations, environmental concerns, and technological development. Considering the surge in e-commerce since the pandemic, the path forward for affordable, responsive supply chains is autonomous last-mile delivery. Drone and robot technologies complement the last-mile delivery's operational requirements and hence should be incorporated to assist truck deliveries. This study develops a bi-objective optimization framework for the integrated planning of Drone-And-Robot-assisted Truck (DART) delivery operations to minimize total delivery cost and maximize customer satisfaction considering a soft time window. Three models, including DART, drone-, and robot-assisted trucks are compared considering different operational situations. The results show that the DART delivery mode outperforms with an increase in the number of demand points. DART is particularly preferred when there is a moderate combination of high-density and distant demand points in last-mile delivery. Numerical experiments confirmed that the robot-assisted delivery model brings about cost-effectiveness in heavily populated areas. On the other hand, the drone-assisted truck model stands out in situations where there is a small number of demand points with high dispersity.", "keywords": [ "Drone", "Truck", "Computer science", "Mile", "Last mile (transportation)", "Robot", "Artificial intelligence", "Automotive engineering", "Engineering", "Geography" ], "cited_by_count": 22, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.eswa.2025.126434" }, { "id": "https://openalex.org/W3047219565", "doi": "10.1016/j.jairtraman.2020.101862", "title": "Estimation of traffic density from drone-based delivery in very low level urban airspace", "year": 2020, "publication_date": "2020-08-05", "type": "article", "language": "en", "authors": [ "Malik Doole", "Joost Ellerbroek", "Jacco M. Hoekstra" ], "first_author": "Malik Doole", "venue": "Journal of Air Transport Management", "publisher": "Elsevier BV", "abstract": "Driven by rising consumer demand, interest is growing in the application of autonomous unmanned aerial vehicles (drones) for the last-mile delivery of small express packages and fast-food meals in cities. To be realised, this would require the Very Low Level (VLL) urban airspace to be able to cope with high traffic densities of commercial delivery drones. The potential benefits of such novel drone-based applications are a reduction of traffic congestion in cities, lower greenhouse gas emissions and more efficient transportation operations. To help realise this concept, programs such as U-Space, the unmanned traffic management system for Europe, are developing important services such as deconfliction management and dynamic capacity management. However, for several of these services, design choices will depend on how, and how extensive they will be used. It therefore becomes important to estimate how many delivery drones would operate in a typical city. This paper aims to provide an estimate by establishing a framework to determine the traffic demand for express drone-based package delivery of five European countries. In addition, a detailed case-study is presented for determining traffic density of express package drone delivery for Paris metropolitan area in order to assess the feasibility from a user's perspective. The paper also discusses the potential of fast-food meal delivery drones compared to traditional delivery modes for Paris. Results suggest that hourly traffic densities culminating from express package and fast-food meal delivery drones will exceed today's global commercial aircraft traffic of 10,000 per day by more than six-fold for just one potential metropolitan city.", "keywords": [ "Drone", "Metropolitan area", "Transport engineering", "Traffic congestion", "Air traffic control", "Order (exchange)", "Air traffic management", "Computer science", "Engineering", "Business", "Geography" ], "cited_by_count": 132, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S0969699719304004/pdf" }, { "id": "https://openalex.org/W2972522542", "doi": "10.23919/acc.2019.8815099", "title": "The Multi-objective Dynamic Traveling Salesman Problem: Last Mile Delivery with Unmanned Aerial Vehicles Assistance", "year": 2019, "publication_date": "2019-07-01", "type": "conference-paper", "language": "en", "authors": [ "Ben Remer", "Andreas A. Malikopoulos" ], "first_author": "Ben Remer", "venue": null, "publisher": null, "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", "Mile", "Computer science", "Last mile (transportation)", "Aeronautics", "Engineering", "Geography", "Algorithm", "Geodesy" ], "cited_by_count": 16, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.23919/acc.2019.8815099" }, { "id": "https://openalex.org/W4399526732", "doi": "10.1109/tits.2024.3408476", "title": "Toward Sustainable Last-Mile Deliveries: A Comparative Study of Energy Consumption and Delivery Time for Drone-Only and Drone-Aided Public Transport Approaches in Urban Areas", "year": 2024, "publication_date": "2024-06-11", "type": "article", "language": "en", "authors": [ "Mohammed Rahmani", "Florian Delavernhe", "Sidi‐Mohammed Senouci", "Marion Berbineau" ], "first_author": "Mohammed Rahmani", "venue": "IEEE Transactions on Intelligent Transportation Systems", "publisher": "Institute of Electrical and Electronics Engineers", "abstract": "The increasing demand for fast and energy-efficient parcel deliveries driven by the growth of e-commerce has made drones an attractive option for urban freight. However, considering drones’ energy usage throughout the entire delivery process is essential when assessing their suitability. This research introduces an energy consumption model encompassing all flight stages—takeoff, flight, landing, hovering—simulating last-mile energy consumption within drone delivery-based systems. Additionally, it conducts a novel comparison between a system relying only on drones (Drone-only system) and a system combining drones with public transportation (Drone-APT system). The comparison considers factors such as consumer distribution, warehouse locations, and drone battery characteristics. The results, based on the real 3D structure of Barcelona, demonstrate that the Drone-APT system maintains consistent power consumption across different consumer distributions and warehouse locations. Conversely, the Drone-only system ensures consistent delivery times in these same scenarios. Furthermore, the Drone-APT improves energy efficiency, especially when direct drone delivery is limited by battery life. However, this efficiency improvement leads to increased delivery time due to the unpredictable timing of public transport vehicles. Striking a balance between drone energy consumption and delivery time is crucial, warranting further research to identify the most sustainable solution for last-mile delivery. This study offers valuable insights into the advantages and trade-offs associated with integrating drones and public transportation, laying the groundwork for future optimization efforts. Future work could incorporate intelligent technologies like machine learning to effectively address these trade-offs by dynamically optimizing drone paths based on energy efficiency and delivery time.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Public transport", "Energy consumption", "Aeronautics", "Transport engineering", "Computer science", "Engineering", "Geography", "Electrical engineering" ], "cited_by_count": 22, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1109/tits.2024.3408476" }, { "id": "https://openalex.org/W3031445336", "doi": "10.1111/poms.13217", "title": "Retail Deliveries by Drones: How Will Logistics Networks Change?", "year": 2020, "publication_date": "2020-05-24", "type": "article", "language": "en", "authors": [ "Sandun C. Perera", "Milind Dawande", "Ganesh Janakiraman", "Vijay S. Mookerjee" ], "first_author": "Sandun C. Perera", "venue": "Production and Operations Management", "publisher": "Wiley", "abstract": "Emerging technologies such as drone delivery services enable retailers to cost‐effectively offer unprecedented delivery speed and adaptable delivery lead times using dedicated aerial vehicles for individual orders. A natural and important question arises: What is the impact of a drone delivery system (DDS) on a retailer’s extant logistics parameters, for example, the number of customer‐facing delivery centers (last‐mile warehouses) it uses and delivery lead times it offers? On the one hand, the ability to reach customers faster than through traditional means argues for more centralization of delivery services. On the other hand, more decentralization can allow the retailer to offer hitherto unheard‐of delivery lead times and thereby spur demand. We show that, as drone technology matures and becomes more cost‐effective, delivery networks will become increasingly decentralized while delivering products at faster speeds. While perfect delivery customization—under which each demand location is offered a customized delivery guarantee—is theoretically feasible under a DDS, it may not be practical to implement such a finely differentiated delivery strategy. Instead, we show that retailers can recover a significant portion of the profit under this ideal scenario by offering limited delivery‐time customization, that is, partitioning the market into a few delivery “zones” and offering the best feasible delivery guarantee for each zone. In physically congested metropolitan markets, where retailers may be forced to operate with only a few delivery centers, it may be optimal to operate a DDS by offering delivery guarantees that are inferior to the best possible in order to throttle unprofitable demand. In such markets, the effectiveness of limited delivery‐time customization increases as the extent of physical congestion increases.", "keywords": [ "Drone", "Business", "Order (exchange)", "Delivery Performance", "Computer science", "Personalization", "Last mile (transportation)", "Operations management", "Marketing", "Process management", "Economics" ], "cited_by_count": 98, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1111/poms.13217" }, { "id": "https://openalex.org/W4400249409", "doi": "10.3390/su16135621", "title": "Consumer Acceptance of Drones for Last-Mile Delivery in Jeddah, Saudi Arabia", "year": 2024, "publication_date": "2024-06-30", "type": "article", "language": "en", "authors": [ "Ghada Talat Alhothali", "Felix Mavondo", "Bader A. Alyoubi", "Haneen Algethami" ], "first_author": "Ghada Talat Alhothali", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "The number of industries using drones is increasing. Although early research was conducted on drones, the prior literature has not emphasized consumer adoption of drones for item delivery. Consequently, this study investigates whether customers are open to receiving packages from drones. This study also examines the elements that influence customers’ willingness to adopt drone package delivery. This study fills a gap in the logistics and service research by examining people’s concerns regarding using drones. The unified theory of acceptance and use of technology (UTAUT2) serves as the basis for the conceptual framework. A self-administered online survey is deployed. The results demonstrate that perceived privacy risks negatively influence performance and effort expectancy as well as facilitating conditions and social influence. This study further validates the UTAUT2 by confirming the influence of performance expectancy and facilitating conditions on attitudes toward adopting drones. Moreover, this study confirms the positive influence of attitude on behavior. This study has managerial implications, one of which is the suggestion that the deployment and use of drones should minimize interference with people’s privacy.", "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Advertising", "Business", "Geography" ], "cited_by_count": 14, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/16/13/5621/pdf?version=1720424467" }, { "id": "https://openalex.org/W3170627891", "doi": "10.7307/ptt.v33i3.3721", "title": "The Application of Drones in City Logistics Concepts", "year": 2021, "publication_date": "2021-06-02", "type": "article", "language": "en", "authors": [ "Snežana Radoman Tadić", "Milovan Kovač", "Olja Čokorilo" ], "first_author": "Snežana Radoman Tadić", "venue": "PROMET - Traffic&Transportation", "publisher": "University of Zagreb, Faculty of Transport and Traffic Sciences", "abstract": "With the rise of city logistics (CL) problems in the last three decades, various methods, approaches, solutions, and initiatives were analyzed and proposed for making logistics in urban areas more sustainable. The most analyzed and promising solutions are those that take into account cooperation among logistics providers and consolidation of the flow of goods. Furthermore, technological innovations enable the implementation of modern vehicles/equipment in order to make CL solutions sustainable. For several years, drone-based delivery has attracted lots of attention in scientific research, but there is a serious gap in the literature regarding the application of drones in CL concepts. The goal of this paper is to analyze four CL concepts that differ in consolidation type, transformation degree of flow of goods (direct and indirect, multi-echelon flows), and the role of drones. Two of the analyzed concepts are novel, which is the main contribution of the paper. The performances of the analyzed concepts are compared to the performances of the traditional delivery model – using only trucks without prior flow consolidation. The results indicate that CL concepts which combine different consolidation models and drones in the last phase of the delivery could stand out as a sustainable CL solution.", "keywords": [ "Consolidation (business)", "Drone", "City logistics", "Truck", "Computer science", "Business", "Process management", "Operations research", "Transport engineering", "Engineering" ], "cited_by_count": 28, "is_retracted": false, "is_paratext": false, "open_access_url": "https://traffic.fpz.hr/index.php/PROMTT/article/download/3721/561561925" }, { "id": "https://openalex.org/W4388265398", "doi": "10.1186/s12544-023-00606-0", "title": "Modelling public attitude towards drone delivery in Germany", "year": 2023, "publication_date": "2023-10-25", "type": "article", "language": "en", "authors": [ "Robin Kellermann", "Tobias Biehle", "Hamid Mostofi" ], "first_author": "Robin Kellermann", "venue": "European Transport Research Review", "publisher": "Springer Science+Business Media", "abstract": "Abstract Background Last-mile delivery by drone is expected to be a promising innovation for future urban logistics. However, in addition to adoption of services by customers, leveraging this delivery method will depend essentially on a positive public perception of such services in urban airspace. Objective This article provides novel and comprehensive insights into factors driving or impeding citizens' attitudes towards drone delivery. Methodology The article develops a structural equation model that derives from a sequential exploratory mixed methods design. In the first step, factors affecting attitudes towards drone delivery were identified within the scope of five focus groups and converted into the development of a questionnaire. In the second step, a German population-representative survey was conducted through telephone interviews, which provided reliable data to test the model (n = 819). Results Expected risks (particularly stress due to traffic in lower airspace, noise, and visual disturbances), as well as expected benefits (particularly fast and time-flexible delivery), significantly affect attitudes towards drone-based delivery, while the individual level of technological openness (technophilia) does not have a significant association. Moreover, the model reveals that the expected risks of drone deliveries are stronger associated with public attitude than with expected benefits. Conclusions The provided framework suggests fashioning policies and drone delivery applications that focus on mitigating social, spatial, and visual risks while achieving maximum utility for customers.", "keywords": [ "Drone", "Openness to experience", "Structural equation modeling", "Business", "Risk perception", "Scope (computer science)", "Population", "Focus group", "Perception", "Marketing", "Transport engineering", "Engineering" ], "cited_by_count": 27, "is_retracted": false, "is_paratext": false, "open_access_url": "https://etrr.springeropen.com/counter/pdf/10.1186/s12544-023-00606-0" }, { "id": "https://openalex.org/W4407772761", "doi": "10.1016/j.aei.2025.103201", "title": "A multistage stochastic programming approach for drone-supported last-mile humanitarian logistics system planning", "year": 2025, "publication_date": "2025-02-20", "type": "article", "language": "en", "authors": [ "Zhongyi Jin", "Kam K.H. Ng", "Chenliang Zhang", "Ying Chan", "Yichen Qin" ], "first_author": "Zhongyi Jin", "venue": "Advanced Engineering Informatics", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Humanitarian Logistics", "Computer science", "Operations research", "Stochastic programming", "Engineering", "Operations management", "Transport engineering", "Mathematical optimization", "Geography" ], "cited_by_count": 19, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.aei.2025.103201" }, { "id": "https://openalex.org/W4400346561", "doi": "10.1016/j.trd.2024.104306", "title": "Exploring noise reduction strategies: Optimizing drone station placement for last-mile delivery", "year": 2024, "publication_date": "2024-07-05", "type": "article", "language": "en", "authors": [ "Qichen Tan", "Jiafan Hou", "Yuhong Li", "Renhao Qu", "Peng Zhan Zhou", "Siyang Zhong", "Hong Kam Lo", "Xin Zhang" ], "first_author": "Qichen Tan", "venue": "Transportation Research Part D Transport and Environment", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Noise reduction", "Reduction (mathematics)", "Computer science", "Noise (video)", "Aeronautics", "Engineering", "Marine engineering", "Telecommunications", "Geography" ], "cited_by_count": 17, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.trd.2024.104306" }, { "id": "https://openalex.org/W2953791940", "doi": null, "title": "Comparative Evaluation of Drone Delivery Systems in Last-Mile Delivery", "year": 2019, "publication_date": "2019-01-01", "type": "article", "language": "en", "authors": [ "Oriol Garcia", "Antonius Santoso" ], "first_author": "Oriol Garcia", "venue": "DSpace@MIT (Massachusetts Institute of Technology)", "publisher": "Massachusetts Institute of Technology", "abstract": "With the latest technological advancement, the use of drones has emerged as an innovative and viable business solution for last-mile distribution. An efficient drone delivery system has to address the classic vehicle routing problem (VRP): \"What is the optimal set of routes for a fleet of drones to serve a given set of customers?.\" The goal of this research project is to evaluate the optimal design and operational performance of four different drone delivery systems, using real-life last-mile truck delivery data. The authors quantitatively model four different drone delivery systems, from a pure drone delivery system to an unsynchronized drone-truck system and compare their relative benefits and shortcomings under various scenarios. A Memetic Algorithm, an extension of a Genetic Algorithm, is developed and used to optimize delivery routes of truck and drones for all the four delivery models. Our research shows that Memetic Algorithm is quite robust handling VRP with 50 customers, yielding only 3.7% gap from the optimal solution. Among the four considered delivery models in this research, the Delivery System model 4 - where truck and drone share same area of service - performs superior than other three models, providing 100% coverage to all customers and reducing minimum tour time as high as 80%. The outcome of this research will help shape the quantitative and qualitative comparison of drone delivery systems and set the foundation for modelling and analysis of more advanced systems (e.g. synchronized truck-drone delivery system). It also helps industry to understand the possible use cases for drones in last-mile delivery and the most crucial levers of these models to maximize the performance of such drone delivery systems.", "keywords": [ "Drone", "Mile", "Last mile (transportation)", "Delivery system", "Computer science", "Engineering", "Geography", "Biology" ], "cited_by_count": 6, "is_retracted": false, "is_paratext": false, "open_access_url": "https://hdl.handle.net/1721.1/121319" }, { "id": "https://openalex.org/W2753728908", "doi": "10.1109/iros.2017.8206607", "title": "An origami-inspired cargo drone", "year": 2017, "publication_date": "2017-09-01", "type": "conference-paper", "language": "en", "authors": [ "Przemyslaw Kornatowski", "Stefano Mintchev", "Dario Floreano" ], "first_author": "Przemyslaw Kornatowski", "venue": null, "publisher": null, "abstract": "Multicopters stand to revolutionize parcel delivery because of their capability to operate in areas with unsuitable road infrastructure and precisely maneuver in cluttered environments. However, current multicopters for delivery can be dangerous for people, and are difficult to store and transport. Safety issues arise because users are exposed to unshielded spinning propellers. Transportation to the place of deployment and storage is often impaired by the large size that is required for heavy lifting. This paper addresses these limitations by proposing the integration of a quadcopter into a foldable protective cage. The cage provides an all-round protective structure that physically separates the propellers from the environment, ensuring the safety of people. The drone and the cage can be easily folded with a single movement, significantly reducing its size for ease of storage and transportation. This design has been validated with a quadcopter that can lift parcels up to 500 g and reduce its storage volume by 92% when folded.", "keywords": [ "Quadcopter", "Drone", "Software deployment", "Computer science", "Lift (data mining)", "Food delivery", "Automotive engineering", "Transport engineering", "Computer security", "Simulation", "Engineering", "Business" ], "cited_by_count": 81, "is_retracted": false, "is_paratext": false, "open_access_url": "http://infoscience.epfl.ch/record/230988" }, { "id": "https://openalex.org/W3202150210", "doi": "10.1016/j.comnet.2023.109626", "title": "A survey on security and privacy issues of UAVs", "year": 2023, "publication_date": "2023-02-10", "type": "article", "language": "en", "authors": [ "Yassine Mekdad", "Ahmet Arış", "Leonardo Babun", "Abdeslam El Fergougui", "Mauro Conti", "Riccardo Lazzeretti", "Arif Selcuk Uluagac" ], "first_author": "Yassine Mekdad", "venue": "Computer Networks", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Computer science", "Computer security", "Security analysis", "Internet privacy" ], "cited_by_count": 239, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.comnet.2023.109626" }, { "id": "https://openalex.org/W4391258698", "doi": "10.3390/su16031060", "title": "Integrating Cargo Bikes and Drones into Last-Mile Deliveries: Insights from Pilot Deliveries in Five Greek Cities", "year": 2024, "publication_date": "2024-01-26", "type": "article", "language": "en", "authors": [ "Κωνσταντίνος Αθανασόπουλος", "Ioannis Chatziioannou", "A.-M. Boutsi", "Georgios Tsingenopoulos", "Sofia Soile", "Regina Chliverou", "Zoe Petrakou", "Efstathios Papanikolaou", "Christos Karolemeas", "Efthymia Kourmpa", "Kalliοpi Papadaki", "Eleftheria Tzika", "Charalabos Ioannidis", "Chryssy Potsiou", "Thanos Vlastos" ], "first_author": "Κωνσταντίνος Αθανασόπουλος", "venue": "Sustainability", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "Currently, there is a growing consensus that the use of more sustainable urban freight transportation has the potential to offer major energy and efficiency benefits which can be achieved through the appropriate combination of cargo bikes and the integration of drones into the urban logistics system. This study presents the results of a stepwise regression analysis that examines the role, benefits, and impact of electric vehicles such as e-bikes, cargo bikes, and drones for intermodal freight transportation in five Greek cities to support the green logistics paradigm. The results show that between routes of almost equal length, the most bicycle-friendly routes, such as routes along pedestrian areas or residential streets, should be avoided, as they reduce delivery speed and increase delivery costs in terms of energy and time expenditure. In addition, priority roads, which usually have higher traffic speeds and more trucks, are preferred by cyclists due to the quality of the road surface, even though the feeling of safety is lower on such roads. Finally, regarding drones, energy consumption is relatively low in the 0–5 mph and 6–10 mph wind speed ranges, indicating efficient energy use. In the 11–15 mph and 16–20 mph wind speed ranges, energy efficiency is significantly lower than the battery capacity, indicating that the cargo drone exhibits excessive energy consumption under these conditions.", "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Aeronautics", "Business", "Transport engineering", "Geography", "Engineering", "Operations management", "Agricultural economics", "Economics" ], "cited_by_count": 21, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2071-1050/16/3/1060/pdf?version=1706241861" }, { "id": "https://openalex.org/W3205388741", "doi": "10.1299/jamdsm.2021jamdsm0069", "title": "Genetic algorithm for scheduling of parcel delivery by drones", "year": 2021, "publication_date": "2021-01-01", "type": "article", "language": "en", "authors": [ "Yohei Hazama", "Hitoshi Iima", "Yoshiyuki Karuno", "Kosuke Mishima" ], "first_author": "Yohei Hazama", "venue": "Journal of Advanced Mechanical Design Systems and Manufacturing", "publisher": "Japan Society Mechanical Engineers", "abstract": "In recent years, efficient logistics has become indispensable, and using unmanned aerial vehicles (UAVs) or drones is promising for considerably reducing the cost and time required for parcel delivery. This paper addresses a parcel delivery scheduling problem. In this problem, a truck loaded with drones and parcels leaves a distribution center and stops at some points on a fixed route. At each point, the drones take off and deliver parcels to customers. We define this problem as finding the assignment of customers to both the drones and their takeoff points. Then, we propose a genetic algorithm (GA) for finding a near-optimal solution in a short time. In the proposed GA, a solution is represented using sets of customers assigned to the takeoff points, and a heuristic rule determines the assignment to the drones. The crossover operation enables offspring to inherit the customer sets. Experimental results show that the proposed GA can successfully find an optimal or a near-optimal solution faster than an integer programming solver for almost all instances. In addition, it significantly outperforms other GAs using a different crossover.", "keywords": [ "Drone", "Crossover", "Genetic algorithm", "Takeoff", "Mathematical optimization", "Scheduling (production processes)", "Computer science", "Job shop scheduling", "Solver", "Heuristic", "Engineering", "Mathematics" ], "cited_by_count": 21, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.jstage.jst.go.jp/article/jamdsm/15/6/15_2021jamdsm0069/_pdf" }, { "id": "https://openalex.org/W4394563636", "doi": "10.3390/systems12040121", "title": "Two-Stage Delivery System for Last Mile Logistics in Rural Areas: Truck–Drone Approach", "year": 2024, "publication_date": "2024-04-06", "type": "article", "language": "en", "authors": [ "Debao Dai", "Hanqi Cai", "Liang Ye", "Wei Shao" ], "first_author": "Debao Dai", "venue": "Systems", "publisher": "Multidisciplinary Digital Publishing Institute", "abstract": "In rural areas of China, the challenges of efficient and cost-effective distribution are exacerbated by underdeveloped infrastructure and low population density, with last mile logistics distribution posing a significant obstacle. To address the gap in drone application for last mile logistics in rural areas, a truck–drone distribution model was developed based on the specific conditions of rural regions. The improved fuzzy C-means algorithm (FCM) and genetic simulated annealing algorithm (GASA) were employed to tackle real−world cases in rural areas. The focus of the truck–drone system is to optimize the rural logistics distribution process, reduce delivery time, and minimize costs while considering factors such as maximum mileage of trucks and drones as well as customer priority. Compared to traditional methods, this system has demonstrated notable improvements in distribution efficiency and cost reduction, offering valuable insights for practical drone applications in last mile rural logistics.", "keywords": [ "Truck", "Drone", "Last mile (transportation)", "Obstacle", "Transport engineering", "Distribution center", "Business", "Mile", "Computer science", "Operations research", "Geography", "Engineering" ], "cited_by_count": 18, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.mdpi.com/2079-8954/12/4/121/pdf?version=1712484291" }, { "id": "https://openalex.org/W4393131813", "doi": "10.1016/j.cie.2024.110096", "title": "Addressing the challenges of using autonomous robots for last-mile delivery", "year": 2024, "publication_date": "2024-03-24", "type": "article", "language": "en", "authors": [ "Ertuğrul Ayyıldız", "Melike Erdoğan" ], "first_author": "Ertuğrul Ayyıldız", "venue": "Computers & Industrial Engineering", "publisher": "Elsevier BV", "abstract": null, "keywords": [ "Pairwise comparison", "Computer science", "Mile", "Drone", "Last mile (transportation)", "Popularity", "Process (computing)", "Investment (military)", "Risk analysis (engineering)", "Business", "Operations management", "Engineering" ], "cited_by_count": 29, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1016/j.cie.2024.110096" }, { "id": "https://openalex.org/W4290990977", "doi": "10.1016/j.trc.2022.103808", "title": "Traffic management and resource allocation for UAV-based parcel delivery in low-altitude urban space", "year": 2022, "publication_date": "2022-08-11", "type": "article", "language": "en", "authors": [ "Ang Li", "Mark M. Hansen", "Bo Zou" ], "first_author": "Ang Li", "venue": "Transportation Research Part C Emerging Technologies", "publisher": "Elsevier BV", "abstract": "This research proposes a framework of Unmanned Aircraft Vehicles (UAV) system traffic management in the context of parcel delivery in low-altitude urban airspace, including clustering-based UAV path planning, Unmanned Aircraft System Traffic Management (UTM) with conflict detection and resolution (CD&R), and mechanism design for airspace resource allocation. For UAV path planning, we develop a procedure by first clustering a large variety of obstacles that arise from building heights and terrain topology and can impede UAV flying. Based on the clustered obstacles, Saturated Fast-Marching Square (Saturated FM2) algorithm is then employed to generate optimal and alternative paths for each UAV mission. While identifying the optimal and alternative paths does not consider UAV traffic interactions, several traffic management models are proposed to efficiently allocate spatial and temporal airspace resources to UAV missions. The UTM models determine the departure time and the path to take for each UAV flight while resolving path conflicts from different perspectives. Specifically, four UTM models are proposed: Sequential Delay (SD) Model, Sequential Delay/Reroute (SDR) Model, Full Optimization (FO) Model, and Batch Optimization (BO) Model. Among the four models, the BO model is of particular interest as it strikes a balance between seeking a system optimum solution and maintaining computational tractability. Given that traffic management requires private information from UAV operators, the Vickrey-Clarke-Groves (VCG) mechanism is further adapted to the UTM context, in which airspace resource allocation is performed in conjunction with a payment scheme to incentivize truthful private information reporting by UAV operators. Extensive numerical analysis is conducted with San Francisco as the case study area. The results show the effectiveness of the proposed framework, particularly the scalability of the BO model. We also find that payment by a UAV flight under the adapted VCG mechanism depends critically on traffic density and the extent of interaction the UAV flight has with other flights.", "keywords": [ "Context (archaeology)", "Computer science", "Resource allocation", "Terrain", "Cluster analysis", "Resource management (computing)", "Path (computing)", "Motion planning", "Real-time computing", "Operations research", "Distributed computing", "Engineering" ], "cited_by_count": 96, "is_retracted": false, "is_paratext": false, "open_access_url": "https://www.sciencedirect.com/science/article/pii/S0968090X22002339/pdf" }, { "id": "https://openalex.org/W4399933877", "doi": "10.26437/ajar.v10i1.677", "title": "Shortening The Last-Mile: Impact of Zipline Medical Drone Delivery on The Operations of Hard-to-Reach Healthcare Facilities in Northern Ghana.", "year": 2024, "publication_date": "2024-06-23", "type": "article", "language": "en", "authors": [ "Oswald Atiga", "Bright Junior Tanzubil", "J. Asaana", "E. C. Ayamba", "Mustapha Torobo Seidu", "I. Mohammed" ], "first_author": "Oswald Atiga", "venue": "African Journal Of Applied Research", "publisher": null, "abstract": "Purpose: This research study investigated the impact of Zipline Medical Drone Delivery on the operations of last-mile healthcare facilities in northern Ghana. Design/Methodology/Approach: The research study adopted an exploratory research design to determine the impact of Zipline’s medical drone delivery on the operations of last-mile healthcare facilities in Northern Ghana. An online survey questionnaire was deployed to collect quantitative data from 159 trained employees of last-mile health facilities who were selected through a purposive sampling technique from last-mile drone-served healthcare facilities. Findings: The study established that drone delivery speed, logistics efficiency and availability of drone delivery resources significantly impacted zipline delivery of medical commodities to last-mile public healthcare facilities in Northern Ghana, reducing commodity delivery lead-time and improving access to essential healthcare supplies for efficient service delivery. Research Limitation/Implications: This research focused mainly on the impact of drone delivery of medical commodities on the operations of last-mile public healthcare facilities in Northern Ghana. Practical Implications: The results of this study show that by enhancing drone delivery speed, logistics efficiency and drone resource availability, the operations of public healthcare facilities can be improved by ensuring that essential medicines are made available, patient waiting time is significantly reduced and outpatient services are improved. Social Implication: The study recommends the establishment of a Zipline-Administrators partnership which will eventually result in a reduction of medical commodity lead-time, improved accessibility of patients to essential health commodity supplies and general cost savings to the community. Originality/Value/Novelty: Although drone technology has been the subject of numerous studies in Ghana, none has investigated the impact of medical commodity drone delivery services on the operations of last-mile healthcare facilities in Northern Ghana. This study therefore explored the impact of drone delivery services from the last-mile healthcare facilities’ perspective.", "keywords": [ "Mile", "Drone", "Last mile (transportation)", "Health care", "Healthcare delivery", "Medical emergency", "Business", "Geography", "Medicine", "Economic growth", "Economics" ], "cited_by_count": 12, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.26437/ajar.v10i1.677" }, { "id": "https://openalex.org/W2616938768", "doi": "10.1007/978-3-319-59513-9_9", "title": "Logistics Support Approach for Drone Delivery Fleet", "year": 2017, "publication_date": "2017-01-01", "type": "conference-paper", "language": "en", "authors": [ "Asma Troudi", "Sid-Ali Addouche", "Sofiène Dellagi", "Abderrahman El Mhamedi" ], "first_author": "Asma Troudi", "venue": "Lecture notes in computer science", "publisher": "Springer Science+Business Media", "abstract": null, "keywords": [ "Drone", "Computer science", "Last mile (transportation)", "City logistics", "Cover (algebra)", "Aeronautics", "Operations research", "Transport engineering", "Mile", "Engineering", "Geography" ], "cited_by_count": 20, "is_retracted": false, "is_paratext": false, "open_access_url": "https://doi.org/10.1007/978-3-319-59513-9_9" } ]