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针对多无人机协同任务分配问题经过单目标简化后对决策处理存在片面性和主观性等问题,提出了一种利用多目标自适应快速人工蜂群算法对其进行处理的方法.首先,建立多目标无人机协同任务分配模型;其次通过建立外部种群的约束处理技术及重置Harmonic平均距离循环策略对自适应快速人工蜂群算法(ABCSGQ)进行改进.另外通过定义自主决策准则引导多目标任务分配的方案选取.仿真实验结果表明:相比于多目标人工蜂群算法及非支配排序遗传算法,改进算法具有较好的分布性、收敛性及更高效的求解能力.
Aiming at the problem of multi-UAV cooperative task assignment after single-objective simplification, this paper proposes a multi-objective adaptive fast artificial bee colony algorithm to process it.First, Target UAV collaborative task assignment model, and second, improve the adaptive fast artificial bee colony algorithm (ABCSGQ) through the establishment of external population constraint processing technology and reset Harmonic average distance cycle strategy.In addition, by the definition of autonomous decision criteria to guide the multi-objective task The results of simulation show that compared with the multi-objective artificial bee colony algorithm and the non-dominated sorting genetic algorithm, the improved algorithm has better distribution, convergence and more efficient solving ability.