面向无人机集群任务分配的DPSO-GA混合优化算法

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中图分类号：TP18；V279 文献标志码：A DOI：10.3969/j.issn.1673-3819.2026.02.004

Abstract：Toaddresstheoptimizationproblemof taskalocation fordroneswarms，animproved hybrid DPSO-GAoptimizationalgorithmisproposed.Thisapproachconstructsacomplexmappingrelationshipfordroneswarmtaskalocationunder temporalconstraints.Itemploysadaptivecosineadjustmentforinertia weightsandlearningrates，whileincorporatingcrossoverand mutationoperations toenhance thealgorithm's global search capability，convergence speed，andacuracytoward extremes.Simulationcomparisons with DPSOandGAalgorithms reveal thatthe proposedalgorithmachievesanaverage fitnessvalue reduction of 50.0% and 10.7% compared toDPSO and GA respectively，with variance reductions of 95.7% and 79.9% compared to DPSO and GA respectively. The confidence interval widths were only 20.7% and 44.8% of those for DPSOandGA，demonstratingthealgorithm'ssignificantsuperiorityinconvergence，stability，andreliabilityoverhecomparisonalgorithms.Thismakes ita valuablereference for solving multi-objective taskalocation problems in UAVswarms.

Key words：UAV swarms；task allocation；temporal constraints；discrete particle swarm；genetic algorithm

纳卡冲突到俄乌冲突的作战实践表明，无人机已由战争配角转变为不可或缺的作战装备。（剩余9759字）