现代电子技术2025，Vol.48Issue(11)：163-168,6.DOI:10.16652/j.issn.1004-373x.2025.11.025
基于改进灰狼优化算法的多无人机应急救援任务分配
Multi-UAV emergency rescue task planning based on improved grey wolf optimization algorithm
摘要
Abstract
A mathematical model of multi-UAV task assignment is proposed,and an improved hybrid algorithm based on particle swarm optimization(PSO)algorithm and grey wolf optimization(GWO)algorithm is designed in order to improve the efficiency of multi-UAV information reconnaissance task in emergency rescue work.The improved algorithm is called CPS-GWO algorithm for short.Firstly,the problem of multi-UAV information reconnaissance task assignment is described as a multiple traveling salesperson problem(MTSP),and a mathematical model is established with the goal of shortest UAV flight range and the least number of UAVs.Then,the Kent chaos mapping and PSO algorithm are introduced to improve the GWO algorithm in the perspectives of population initialization and search strategy,respectively,and the CPS-GWO algorithm for solving MTSP is designed.Finally,on the basis of six sets of instance data TSPLIB,the UAV task allocation scheme for each of the instances when applying the CPS-GWO algorithm is obtained by Matlab simulation experiments,and the results are compared with those obtained by the improved GWO algorithm proposed in the existing research in the case of the same instance.The results verify the effectiveness and feasibility of the CPS-GWO algorithm for solving MTSP.关键词
无人机/应急救援/任务分配/粒子群优化算法/灰狼优化算法/Kent混沌映射/多旅行商问题Key words
UAV/emergency rescue/task assignment/PSO algorithm/GWO algorithm/Kent chaotic mapping/MTSP分类
电子信息工程引用本文复制引用
田宇,唐阳山,李冬月,任鑫珊,刘建明..基于改进灰狼优化算法的多无人机应急救援任务分配[J].现代电子技术,2025,48(11):163-168,6.基金项目
辽宁省教育厅2023基本科研项目:基于BDS/UAV的道路应急救援目标智能识别与路径规划研究(JYTMS20230842) （JYTMS20230842）
