基于改进遗传算子的多异构无人机静态任务分配算法

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中图分类号：E919 文献标志码：A DOI：10.3969/j. issn.1673-3819.2025.06.006

引用格式：.基于改进遗传算子的多异构无人机静态任务分配算法[J].指挥控制与仿真，2025，47（6）：39-45.WANG C F.Statictaskalocationalgorithmforulti-eterogeneousUAVsbasedonimprovedgeneticoperatorsJ].CommandControl&Simulation，2025，47（6） ：39-45.

Abstract：Toadresstheissues ofinsuficient globaloptimalityandrobustnessintraditional missonplanningforunanned aerialvehicles（UAVs）inurbandisasterreliefscenarios，thispaperproposesamulti-heterogeneousUAVstatictaskallocationalgorithmbased on improved geneticoperators.Byenhancing geneticoperators，designing afunctionallcoupled chromosome encoding strategy，introducing adaptive crossverand mutation mechanisms，and embedding a path planning module into thetaskalocationalgorithm，theaccuracyofthetask allcatiocostfunctioncalculationisimproved.This efectivelyovercomesthe drawbacks of traditional methods，such as inacurate alocationresults due topath cost estimation deviations， as well as poor global optimization and robustness.

KeyWords：path planning；heterogeneous UAV constraint；genetic algorithm；task allocation

随着无人机（UnmannedAerialVehicle，UAV）技术的快速发展，其在灾害救援[1]、物流配送[2]、环境监测[3]等城市复杂场景中的应用日益广泛。（剩余8786字）