指挥控制与仿真2026，Vol.48Issue(2)：30-37,8.DOI:10.3969/j.issn.1673-3819.2026.02.004
面向无人机集群任务分配的DPSO-GA混合优化算法
A hybrid DPSO-GA optimization algorithm for task allocation in UAV swarms
摘要
Abstract
To address the optimization problem of task allocation for drone swarms,an improved hybrid DPSO-GA optimiza-tion algorithm is proposed.This approach constructs a complex mapping relationship for drone swarm task allocation under temporal constraints.It employs adaptive cosine adjustment for inertia weights and learning rates,while incorporating cross-over and mutation operations to enhance the algorithm's global search capability,convergence speed,and accuracy toward extremes.Simulation comparisons with DPSO and GA algorithms reveal that the proposed algorithm achieves an average fit-ness value reduction of 50.0%and 10.7%compared to DPSO 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 DPSO and GA,demonstrating the algorithm's significant superiority in convergence,stability,and reliability over the com-parison algorithms.This makes it a valuable reference for solving multi-objective task allocation problems in UAV swarms.关键词
无人机集群/任务分配/时序约束/离散粒子群/遗传算法Key words
UAV swarms/task allocation/temporal constraints/discrete particle swarm/genetic algorithm分类
信息技术与安全科学引用本文复制引用
沈延安,孙昊,王耀..面向无人机集群任务分配的DPSO-GA混合优化算法[J].指挥控制与仿真,2026,48(2):30-37,8.
