低空经济下车辆与无人机协同配送路径优化研究综述

左大发, 朱德龙, 朱娜娜

包装工程(技术栏目) ›› 2025, Vol. 46 ›› Issue (19) : 298-310.

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包装工程(技术栏目) ›› 2025, Vol. 46 ›› Issue (19) : 298-310. DOI: 10.19554/j.cnki.1001-3563.2025.19.032
绿色包装与循环经济

低空经济下车辆与无人机协同配送路径优化研究综述

  • 左大发, 朱德龙*, 朱娜娜
作者信息 +

Review of Research on the Optimization of Collaborative Distribution Routes between Vehicles and UAVs in Low-altitude Economy

  • ZUO Dafa, ZHU Delong*, ZHU Nana
Author information +
文章历史 +

摘要

目的 探讨车辆与无人机协同配送模式在提升物流配送效率及优化“最后一公里”配送问题中的应用潜力与可行性。方法 提出5种主要协同配送模式,包括平行配送、集中式协同配送、移动起降协同配送、异构车辆无人机协同配送、多车多机协同配送,并对其路径规划算法进行分类和比较,分析其适用性与优劣,同时梳理测试数据集及其应用。结果 各配送模式在效率与场景适配上各有优势,不同路径规划算法在精度、计算效率等方面对配送效果的影响显著,明确了算法的适配性及优化方向。结论 随着路径规划算法和调度系统的进步,车辆与无人机协同配送将在未来智慧物流中发挥关键作用,有望提升系统智能化水平,助力绿色、高效物流发展。

Abstract

The work aims to explore the application potential and feasibility of vehicle and UAV cooperative distribution modes in improving logistics and distribution efficiency and optimizing the "last-mile" distribution. Five major cooperative distribution modes were proposed, including parallel distribution, centralized cooperative distribution, mobile take-off and landing cooperative distribution, heterogeneous vehicle-unmanned aircraft cooperative distribution, and multi-vehicle-multi-aircraft cooperative distribution, and their route planning algorithms were classified and compared to analyze their applicability, strengths and weaknesses, and at the same time, the test datasets and their applications were sorted out. Each distribution mode had its own advantages in terms of efficiency and scene adaptation, and different route planning algorithms had a significant impact on the distribution effect in terms of accuracy and computational efficiency. The adaptability and optimization direction of the algorithms were clarified. With the advancement of route planning algorithms and scheduling systems, the cooperative distribution between vehicles and UAVs will play a key role in future smart logistics, which is expected to improve the system's intelligence level and help the development of green and efficient logistics.

关键词

低空经济 / 无人机配送 / “最后一公里” / 车辆与无人机协同 / 路径规划

Key words

low-altitude economy / UAV distribution / "last mile" / vehicle and UAV cooperative distribution / route planning

引用本文

导出引用
左大发, 朱德龙, 朱娜娜. 低空经济下车辆与无人机协同配送路径优化研究综述[J]. 包装工程(技术栏目). 2025, 46(19): 298-310 https://doi.org/10.19554/j.cnki.1001-3563.2025.19.032
ZUO Dafa, ZHU Delong, ZHU Nana. Review of Research on the Optimization of Collaborative Distribution Routes between Vehicles and UAVs in Low-altitude Economy[J]. Packaging Engineering. 2025, 46(19): 298-310 https://doi.org/10.19554/j.cnki.1001-3563.2025.19.032
中图分类号: U116.1    TB48   

参考文献

[1] 胡巧丽, 兰建义. B2C电子商务企业的成本控制——以京东商城为例[J]. 商场现代化, 2020(24): 20-22.
HU Q L, LAN J Y.Cost Control of B2C E-Commerce Enterprises - Taking JD.COM Mall as an Example[J]. Market Modernization, 2020(24): 20-22.
[2] 葛思诗. 电商物流最后一公里配送问题研究[J]. 物流工程与管理, 2021, 43(2): 81-84.
GE S S.Research on the Last Mile Delivery of E-Commerce Logistics[J]. Logistics Engineering and Management, 2021, 43(2): 81-84.
[3] DUAN J, LUO H, WANG G.Approaches to the Truck-Drone Routing Problem: A Systematic Review[J]. Swarm and Evolutionary Computation, 2025, 9(2): 18-25.
[4] DENG J, HUA J, SHAW B R.Drones Activity in Epidemic Prevention and Prospects in the Post-COVID-19[J]. Springer Singapore, 2022, 41(2): 33-43.
[5] MURRAY C C, CHU G A.The Flying Sidekick Traveling Salesman Problem: Optimization of Drone-Assisted Parcel Delivery[J]. Transportation Research Part C, 2015, 5(4): 86-109.
[6] AGATZ N, BOUMAN P, SCHMIDT M.Optimization Approaches for the Traveling Salesman Problem with Drone[J]. Transportation Science, 2018, 52(4): 965-981.
[7] JOHN G C, SONG S Y.Coordinated Logistics with a Truck and a Drone[J]. Management ScieNce, 2017, 64(9): 52-69.
[8] DING Y D, WAN J Q, LIN W, et al.Coordinated Last-Mile Deliveries with Trucks and Drones: A Comparative Study of Operational Modes[J]. Journal of the Air Transport Research Society, 2024, 3: 100025.
[9] 张萌, 孙璐璐, 苏兵, 等. 考虑空载损失的非集中式共同配送订单分派及路径优化研究[J]. 工业工程, 2024, 27(2): 107-118.
ZHANG M, SUN L L, SU B, et al.Order Dispatching and Routing for Decentralized Joint Distribution Considering Empty-Loading Losses[J]. Industrial Engineering Journal, 2024, 27(2): 107-118.
[10] 刘正元, 王清华. 无人机和车辆协同配送映射模式综述与展望[J]. 系统工程与电子技术, 2023, 45(3): 785-796.
LIU Z Y, WANG Q H.Review and Prospect under the Mapping Mode of Coordinated Delivery of Drones and Vehicles[J]. Systems Engineering and Electronics, 2023, 45(3): 785-796.
[11] DELLAMICO M, MONTEMANNI R, NOVELLANI S.Matheuristic Algorithms for the Parallel Drone Scheduling Traveling Salesman Problem[J]. Annals of Operations Research, 2020, 289(2): 211-226.
[12] KIM S, MOON I.Traveling Salesman Problem with a Drone Station[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 49(1): 42-52.
[13] ALKOUZ B, ABUSAFIA A, LAKHDARI A, et al.In-Flight Energy-Driven Composition of Drone Swarm Services[J]. IEEE Transactions on Services Computing, 2023, 16(3): 1919-1933.
[14] ZHOU L Y, SILVA D F, SMITH A E.Locating Drone Stations for a Truck-Drone Delivery System in Continuous Space[J]. IEEE Transactions on Evolutionary Computation, 2025, 29(1): 158-171.
[15] HAM A M.Integrated Scheduling of M-Truck, M-Drone, and M-Depot Constrained by Time-Window, Drop-Pickup, and M-Visit Using Constraint Programming[J]. Transportation Research Part C: Emerging Technologies, 2018, 9(1): 1-14.
[16] POIKONEN S, GOLDEN B.Multi-Visit Drone Routing Problem[J]. Computers & Operations Research, 2020, 113: 104802.
[17] MOMENI M, MIRZAPOUR AL-E-HASHEM S M J, HEIDARI A. RETRACTED ARTICLE: A New Truck-Drone Routing Problem for Parcel Delivery by Considering Energy Consumption and Altitude[J]. Annals of Operations Research, 2024, 337(1): 1-47.
[18] GÓMEZ-LAGOS J, CANDIA-VÉJAR A, ENCINA F. A New Truck-Drone Routing Problem for Parcel Delivery Services Aided by Parking Lots[J]. IEEE Access, 2021, 9: 11091-11108.
[19] MIGUEL J L, PL G.A Multi-agent Approach to the Truck Multi-Drone Routing Problem[J]. Expert Systems with Applications, 2022, 19(5): 1-16.
[20] LI Y S, ZHANG G Z, PANG Z B, et al.Continuum Approximation Models for Joint Delivery Systems Using Trucks and Drones[J]. Enterprise Information Systems, 2020, 14(4): 406-435.
[21] HAN Y Q, LI J Q, LIU Z M, et al.Metaheuristic Algorithm for Solving the Multi-Objective Vehicle Routing Problem with Time Window and Drones[J]. International Journal of Advanced Robotic Systems, 2020, 17(2): 172988142092003.
[22] CUI H P, LI K Y, JIA S, et al.Dynamic Collaborative Truck-Drone Delivery with Enroute Synchronization and Random Requests[J]. Transportation Research Part E: Logistics and Transportation Review, 2024, 10(38): 66-89.
[23] MOHAMED R, SALAMA S S.Collaborative Truck Multi-Drone Routing and Scheduling Problem: Package Delivery with Flexible Launch and Recovery Sites[J]. Transportation Research Part E: Logistics and Transportation Review, 2022, 20(18): 86-99.
[24] MARINELLI M, CAGGIANI L, OTTOMANELLI M, et al.En Route Truck-Drone Parcel Delivery for Optimal Vehicle Routing Strategies[J]. IET Intelligent Transport Systems, 2018, 12(4): 253-261.
[25] DAVID S, DAVID P, STEFAN R, An Adaptive Large Neighborhood Search Metaheuristic for the Vehicle Routing Problem with Drones[J]. Transportation Research Part C: Emerging Technologies, 2019, 102(4): 289-315
[26] FREITAS J C, PENNA P H V, TOFFOLO T A M. Exact and Heuristic Approaches to Truck-Drone Delivery Problems[J]. EURO Journal on Transportation and Logistics, 2023, 12: 100094.
[27] IlKE B, GIZEM O, Optimizing Drone-Assisted Last-Mile Deliveries: The Vehicle Routing Problem with Flexible Drones[J]. Optimization Online. 2020, 4(9): 1-28.
[28] POIKONEN S, WANG X Y, GOLDEN B.The Vehicle Routing Problem with Drones: Extended Models and Connections[J]. Networks, 2017, 70(1): 34-43.
[29] PATCHARA K, MARIO V, MOHAMMAD M, et al.Multiple Traveling Sales-Man Problem with Drones: Mathematical Model and Heuristic Approach[J]. Computers & Industrial Engineer, 2019, 12(9): 14-30.
[30] BRUNI M E, KHODAPARASTI S.K, MOSHREF J M. A Logic-Based Benders Decomposition Method for the Multi-Trip Traveling Repairman Problem with Drones[J]. Computers and Operations Research, 2022, 145.
[31] NGUYEN M A, DANG G T, MINH HOÀNG H, et al. The Min-Cost Parallel Drone Scheduling Vehicle Routing Problem[J]. European Journal of Operational Research, 2022, 299(3): 910-930.
[32] WANG D S, HU P, DU J X, et al.Routing and Scheduling for Hybrid Truck-Drone Collaborative Parcel Delivery with Independent and Truck-Carried Drones[J]. IEEE Internet of Things Journal, 2019, 6(6): 10483-10495.
[33] DUKKANCI O, KARA B Y, BEKTAŞ T.Minimizing Energy and Cost in Range-Limited Drone Deliveries with Speed Optimization[J]. Transportation Research Part C: Emerging Technologies, 2021, 125: 102985.
[34] SCHERMER D, MOEINI M, WENDT O.A Matheuristic for the Vehicle Routing Problem with Drones and Its Variants[J]. Transportation Research Part C: Emerging Technologies, 2019, 106: 166-204.
[35] YUREK E, OZMUTLU H C.A Decomposition-Based Iterative Optimization Algorithm for Traveling Salesman Problem with Drone[J]. Transportation Research Part C: Emerging Technologies, 2018, 91: 249-262.
[36] DANIEL S, MAHID M, OLIVER W.The Traveling Salesman Drone Station Location Problem[J]. World Congress on Global Optimization, 2019, 15(7): 1129-1138.
[37] CHENG C, ADULYASAK Y, ROUSSEAU L.Drone Routing with Energy Function: Formulation and Exact Algorithm[J]. Transportation Research Part B, 2020, 13(9): 364-387.
[38] KANG M, LEE C.An Exact Algorithm for Heterogeneous Drone-Truck Routing Problem[J]. Transportation Science, 2021, 55(5): 1088-1112.
[39] WANG Y, WANG Z, HU X P, et al.Truck-Drone Hybrid Routing Problem with Time-Dependent Road Travel Time[J]. Transportation Research Part C, 2022, 144.
[40] WANG Y, YANG S, WANG X V, et al.Research on Truck-Drone Collaborative Route Planning for Rural Logistics Delivery Services[J]. Scientific Reports, 2024, 14: 31815.
[41] WEI Y H, WANG Y, HU X P.The Two-Echelon Truck-Unmanned Ground Vehicle Routing Problem with Time-Dependent Travel Times[J]. Transportation Research Part E, 2025, 194, 103954.
[42] FAN W H, SU Y, LIU J, et al.Joint Task Offloading and Resource Allocation for Vehicular Edge Computing Based on V2I and V2V Modes[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(4): 4277-4292.
[43] NA Y W, LI Y L, CHEN D Q, et al.Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm Optimization[J]. Sustainability, 2023, 15(16): 12101.
[44] BENGIO Y, LODI A, PROUVOST A.Machine Learning for Combinatorial Optimization: A Methodological Tour d'horizon[J]. European Journal of Operational Research, 2021, 290(2): 405-421.
[45] 孔维仁, 周德云, 赵艺阳, 等. 基于深度强化学习与自学习的多无人机近距空战机动策略生成算法[J]. 控制理论与应用, 2022, 39(2): 352-362.
KONG W R, ZHOU D Y, ZHAO Y Y, et al.Maneuvering Strategy Generation Algorithm for Multi-UAV in Close-Range Air Combat Based on Deep Reinforcement Learning and Self-Play[J]. Control Theory & Applications, 2022, 39(2): 352-362.
[46] QIE H, SHI D X, SHEN T L, et al.Joint Optimization of Multi-UAV Target Assignment and Path Planning Based on Multi-Agent Reinforcement Learning[J]. IEEE Access, 2019, 7: 146264-146272.
[47] BI Z L, GUO X W, WANG J C, et al.Deep Reinforcement Learning for Truck-Drone Delivery Problem[J]. Drones, 2023, 7(7): 445.
[48] LI X H, YAN P Y, YU K Z, et al.Parcel Consolidation Approach and Routing Algorithm for Last-Mile Delivery by Unmanned Aerial Vehicles[J]. Expert Systems with Applications, 2024, 238: 122149.
[49] ARISHI A, KRISHNAN K, ARISHI M.Machine Learning Approach for Truck-Drones Based Last-Mile Delivery in the Era of Industry 4.0[J]. Engineering Applications of Artificial Intelligence, 2022, 116: 105439.
[50] YU F H, CHEN M J, XIA X Y, et al.Logistics Distribution Route Optimization with Time Windows Based on Multi-Agent Deep Reinforcement Learning[J]. International Journal of Information Technologies and Systems Approach, 2024, 17(1): 1-23.
[51] CICEK D, SIMSEK M, KANTARCI B.Machine Learning-Driven Truck-Drone Collaborative Delivery for Time and Energy-Efficient Last-Mile Deliveries[J]. Electronics, 2025, 14(10): 2026.
[52] BI Z L, GUO X W, WANG J C, et al.Truck-Drone Delivery Optimization Based on Multi-Agent Reinforcement Learning[J]. Drones, 2024, 8(1): 27.
[53] 吴瑶, 周愉峰, 李峰. 订单可拆分的低碳冷链配送选址与多车舱路径优化[J]. 计算机工程与应用, 2025, 61(8): 339-350.
WU Y, ZHOU Y F, LI F.Optimization of Low-Carbon Location and Routing Problem with Multi-Compartment for Cold Chain Distribution Considering Order Splitting[J]. Computer Engineering and Applications, 2025, 61(8): 339-350.
[54] MENG Z Y, ZHOU Y T, LI E Y, et al.Environmental and Economic Impacts of Drone-Assisted Truck Delivery under the Carbon Market Price[J]. Journal of Cleaner Production, 2023, 401: 136758.
[55] WALEED N, CLAUDIA A, ALI D.Collaborative Truck-and- Drone Delivery for Inventory-Routing Problems[J]. Transportation Research Part C, 2023, 14(6). 103791.
[56] ZHANG R W, DOU L H, XIN B, et al.A Review on the Truck and Drone Cooperative Delivery Problem[J]. Unmanned Systems, 2024, 12(5): 823-847.
[57] YAHIA H S, MOHAMMED A S.Path Planning Optimization in Unmanned Aerial Vehicles Using Meta-Heuristic Algorithms: A Systematic Review[J]. Environmental Monitoring and Assessment, 2022, 195(1): 30.
[58] PAL O K, SHOVON M S H, MRIDHA M F, et al. In-Depth Review of AI-Enabled Unmanned Aerial Vehicles: Trends, Vision, and Challenges[J]. Discover Artificial Intelligence, 2024, 4(1): 97.

基金

湖北省教育科学规划基金(2023GB033); 教育部高等教育司产学育人项目(240902690 052919); 湖北汽车工业学院博士研究基金(BK202312)

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