Cooperative Multi-task Assignment of Multiple UAVs with Improved Genetic Algorithm Based on Beetle Antennae Search

With the number of UAVs and targets increasing, the quantity of task combinations increases exponentially. This article presents an improved genetic algorithm based on the beetle antennae search algorithm to Multi-UAV task allocation. Firstly, a target sequence is searched through beetle antennae search algorithm, and then the method of twice crossing operators is used to increase the diversity of the target sequence arrangements and retain the global optimality of the population. Finally, the method of dynamically adjusting the mutation probability is used to increase the local search ability of the algorithm to avoid locally optimal. In the simulation part, the effect of the proposed algorithm, both on searching capability and convergence speed, is demonstrated by comparison with other algorithms. The results show that the proposed algorithm outperforms other algorithms in solving the problem of Multi-UAV task allocation.