基于CMA-ES算法的无人机群协同救援任务分配优化

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DOI：10.16652/j.issn.1004-373x.2025.10.015 引用格式：，，.基于CMA-ES算法的无人机群协同救援任务分配优化[J].现代电子技术，2025，48（10）：92-96.

关键词：CMA-ES；无人机；协同任务分配；优化算法；目标函数；约束条件；最大航程中图分类号：TN820.4-34；TP273 文献标识码：A 文章编号：1004-373X（2025）10-0092-05

Abstract：Thealocationof rescue tasksshouldnotonlyconsider theshortest navigation distanceof unmannedaerial vehicle（UAV），butalsominimizetheaveragewaitingtimeofsurvivors，whichisamulti-objectiveoptimizationproblem.Inoder tofindtheoptialsoutioninmulti-objectivesenarios，amethodofcolaborativerescuetaskallcationotimizationbasedon covariance matrixadaptationevolutionarystrategy（CMA-ES）algorithmforUAVswam isproposed.Taking theaverage waiting timeand theshortestsailing distanceasobjectivefunctions，andconsideringconstraintssuchasthemaximumsailingdistance， taskcounts，colaborativeplanningandloadcapacityofUAV，aCMA-ESalgorithmisusedtofindtheoptimalsolutionof the objectivefunctionbymeansoftheparameteroptimization mechanismbasedonnormaldistributioninmultidimensional space， efectivelyresolvingconflictsbetweendiferentobjectivesandachievingmulti-objectivetaskalocationoptimization.The experimentalresultsshowthattheproposedmethodcanalocaterescuetasksreasonably，andensurethatsurvivorscanquickly obtain supplies. The UAV navigates an average of 48.7 km，survivors wait an average of 33.4min ，and rescue tasks are completed in an average of 61.2min

Keywords：CMA-ES；UAV；colaborativetask allcation；optimizationalgorithm；objective function；constraintcondition; maximum flight distance

0 引言

在紧急救援任务中，无人机群展现出了巨大的潜力和价值。（剩余5193字）