针对多无人机多目标任务分配问题, 用一种改进的自适应变权重粒子群优化(AMPSO)算法寻找最优分配方案。涉及联盟组建的任务分配问题较为复杂, 目前尚不能有效获得最优解。用分配优先权机制处理联盟成员剩余资源不确定的问题, 并建立种群粒子和任务分配方案间的映射关系。通过仿真验证, 用AMPSO算法可以快速获得多机多目标最优任务分配方案。

As to the task allocation of multiple UAVs to multiple targets, an improved Adaptive Mutation Particle Swarm Optimization (AMPSO) algorithm was used to seek the optimal allocation scheme. The problem of task allocation would be relatively complex if it is related to league formation, and it is impossible to obtain the optimal solution effectively right now. The mechanism of allocation priority was used to deal with the uncertainty about the remaining resources of the league members. The mapping relation between the population particles and the task-allocation scheme was established. The simulation verified that: by using AMPSO algorithm, the optimal scheme can be quickly obtained for multi-UAV to multi-target task allocation.