基于改进QACA的无人机集群任务分配算法

针对无人机集群多目标任务分配问题,提出在量子蚁群算法(QACA)基础上,融合克隆选择算法的交叉和克隆复制因子来提高算法的全局搜索能力,避免搜索过程陷入早熟收敛问题,然后利用量子蚁群算法快速搜索。仿真结果表明,该算法是求解无人机集群多目标任务分配的一种有效算法。

Task Assignment Algorithm of UAV Cluster Based on Improved QACA

In order to solve the problem of multi-objective task assignment in UAV cluster, a novel algorithm based on quantum ant colony algorithm (QACA) was proposed to improve the global search ability of the algorithm by integrating the crossover and cloning replicators of the clone selection algorithm to avoid premature convergence in the search process. Simulation results show that this algorithm is an effective algorithm for multi-objective task assignment of UAV cluster.