Article Details

Abstract

This study investigates multi-UAV cooperative operations under urban drone logistics service processes. It clarifies the end-to-end workflow, including order generation, loading and takeoff preparation, en-route delivery, service completion, and return for recharging or battery swapping. Key constraints are extracted and integrated into a unified task assignment and scheduling model, including task time windows, vertiport service capacity and operational sequencing, as well as UAV range and energy limitations, with the objective of minimizing total completion time and overall delay. A solution method combining Earliest Due Date (EDD) ordering and heuristic assignment is developed. Simulation experiments compare strategies with and without process constraints, validating the feasibility and effectiveness of the proposed model and method in terms of makespan, on-time rate, and UAV utilization.

Keywords

urban UAV logistics; logistics service process; task assignment and scheduling; time windows and vertiport capacity

References

1. [1] THIPPHAVONG P，APAZA R，BARMORE B，et al. Urban air mobility airspace integration concepts and considerations [C]//AIAA. 2018 Aviation Technology, Integration, and Operations Conference. Reston：AIAA，2018：3676-3681.
2. [2] Zhang Honghai, Zou Yiyuan, Zhang Qiqian, etc A Review of Future Urban Air Traffic Management Research [J]. Acta Aeronautica Sinica, 2021, 42 (7): 82-106
3. [3] ESCRIBANO M J，KHALIFE C，SLIM J，et al. An Integrated Vertiport Placement Model Considering Vehicle Sizing and Queuing: A Case Study in London [J/OL].Journal of Air Transport Management，2023，113：102486（2023-08-18）.https://doi.org/10.1016/j.jairtraman.2023.102486.
4. [4] ABDELJAWED S，EUCHI J，SIARRY P. Vehicle routing with multiple UAVs for the last-mile logistics distribution problem: hybrid distributed optimization [J/OL].Annals of Operations Research，2024，351（1）：1-41.
5. [5] LU F Q，LIU J L，BI H L. Drone–Rider Joint Delivery Routing with Arc Obstacle Avoidance [J/OL].Applied Sciences，2025，15（21）：11469（2025-10-27）.https://doi.org/10.3390/app152111469.
6. [6] Wu Yuhan, Li Junli, Mao Jianlin, etc Multi UAV Balanced Task Allocation Method for Urban Logistics [J/OL]. Journal of Yunnan University (Natural Science Edition), 2025:1-15
7. [7] Li Han, Zhang Honghai, Zhang Liandong, etc Collaborative task allocation of multi logistics unmanned aerial vehicles in urban areas [J]. Systems Engineering and Electronic Technology, 2021, 43 (12): 3594-3602
8. [8] Huang Jin, Peng Hao, Liu Haobin, etc Multi UAV collaborative task allocation based on improved ant colony algorithm [J]. Aviation Computing Technology, 2024, 54 (5): 27-32
9. [9] Ren Xinhui, Rui Yuqi Logistics drone scheduling model based on delivery service mode and path strategy [J]. Journal of Beijing Jiaotong University, 2024, 48 (3): 1-14
10. [10] Zhang Shuqin, Xia Hongshan, Jiang Wei, etc Urban logistics drone assignment based on HSBSO algorithm [J]. Computer Engineering and Applications, 2025, 61 (17): 355-364

Funding

Civil Aviation Safety Capacity Building Fund Project (Research on Network Air Ground Coordination Planning and Service Process Specification for Urban Logistics Drone Takeoff and Landing Airports)

About the authors

Wang Changjin (1982-), male, from Huai'an, Jiangsu, is a senior inspector and a master's student. His research direction is low altitude flight operation management; Ren Mingxuan (2001-), male, Han ethnicity, from Zibo, Shandong, is currently pursuing a master's degree in urban air traffic; Hua Mingzhuang (1995-), male, Han ethnicity, from Shuyang, Jiangsu, lecturer, PhD, research direction: low altitude operation management.