铁道运输与经济2025，Vol.47Issue(10)：60-72,13.DOI:10.16668/j.cnki.issn.1003-1421.2025.10.06
需求不确定下卡车-无人机协同的路径优化研究
Research on Path Optimization of Truck-Drone Collaboration under Uncertain Demand
摘要
Abstract
In response to the fluctuation of emergency material demand in some disaster-stricken areas after the occurrence of emergencies,research was conducted on the path optimization problem of truck-drone collaboration under uncertain demand to improve the efficiency of emergency material distribution.Firstly,the parameter of uncertain demand level was introduced,and a robust path optimization model for the collaboration between trucks and drones was constructed.Secondly,an improved adaptive large neighborhood search algorithm(IALNS)was proposed.This algorithm enhanced solution diversity by designing diversified removal and repair operators and updated the solution through a simulated annealing process to ensure its convergence.Then,the Solomon benchmark was employed to evaluate the algorithm's effectiveness,and the algorithm was compared with the traditional genetic algorithm(GA)and particle swarm optimization(PSO)algorithm.The average GAP of GA,PSO,and IALNS algorithms was 15.18%and 12.91%,respectively,verifying the reliability of the algorithm.Finally,sensitivity analysis was conducted on uncertain level parameters of demand,drone load capacity,and range.The experimental results show that the robust optimization model and IALNS algorithm can ensure the feasibility of the truck-drone path at the disaster-stricken site under demand fluctuations.关键词
路径优化/卡车-无人机协同/需求不确定/自适应大规模邻域搜索算法Key words
Path Optimization/Truck-Drone Collaboration/Uncertain Demand/Adaptive Large Scale Neighborhood Search Algorithm分类
交通工程引用本文复制引用
陈兆芳,李文静,黄文翰..需求不确定下卡车-无人机协同的路径优化研究[J].铁道运输与经济,2025,47(10):60-72,13.基金项目
福建省社会科学规划重点项目(FJ2024MGCA027) （FJ2024MGCA027）
福建省科协科技创新智库课题(FJKX-2024XKB014) （FJKX-2024XKB014）
