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

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。

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.