火力与指挥控制2024,Vol.49Issue(9) :25-31.DOI:10.3969/j.issn.1002-0640.2024.09.004

无人机集群基于多目标的速度决策与任务分配

Velocity Decision-making and Task Allocation of UAV Swarm Based on Multi-objective Optimization

罗轸柳 张娟 李辉
火力与指挥控制2024,Vol.49Issue(9) :25-31.DOI:10.3969/j.issn.1002-0640.2024.09.004

无人机集群基于多目标的速度决策与任务分配

Velocity Decision-making and Task Allocation of UAV Swarm Based on Multi-objective Optimization

罗轸柳 1张娟 1李辉1
扫码查看

作者信息

  • 1. 四川大学计算机学院,成都 610065
  • 折叠

摘要

针对无人机集群作战中如何分配打击目标的问题,将协同多任务分配模型CMTAP提升为两个维度的目标:时间窗适应度和油料消耗,将CMTAP问题的求解维度从分配任务序列拓展到了求解任务序列的对应速度和每架无人机的出发时间确定.针对该问题提出了CMTAP-MO-GA算法,其采用了一种破碎任务序列的染色体变异机制,和一种缺陷修复的染色体交叉机制.该算法能求解出问题在二维目标函数上的帕累托前沿,并获得前沿上每个解对应的分配结果及每个解的执行策略.

Abstract

Addressing the issue of how to allocate the strike targets in UAV swarm operations,the CMTAP(Cooperative Multiple Task Allocation Problem)has been enhanced with two dimensions of objec-tives:time window fitness and fuel consumption.This extension expands the problem-solving dimension of CMTAP from allocating task sequences to solving the corresponding velocities and departure times for each UAV.To tackle this problem,the CMTAP-MO-GA algorithm is proposed.A chromosome mutation mechanism that breaks down task sequences and a chiasmatypy mechanism that repairs deficiencies are utilized.This algorithm can solve the pareto frontier of the problem on a two-dimensional objective func-tion,the corresponding allocation results and the execution policy of every solution on the frontier.

关键词

CMTAP/多目标优化/无人机集群/遗传算法/速度决策

Key words

CMTAP/multi-objective optimization/swarm of UAVs/genetic algorithm/velocity decision-making

引用本文复制引用

基金项目

国家自然科学基金资助项目(U20A20161)

出版年

2024
火力与指挥控制
火力与指挥控制研究会,火力与指挥控制专业情报网

火力与指挥控制

CSTPCDCSCD北大核心
影响因子:0.312
ISSN:1002-0640
参考文献量15
段落导航相关论文