基于多目标遗传算法的异构无人机协同察打

Multiple Heterogeneous UAVs Cooperative Searching and Attacking Based on Parallel NSGA-Ⅱ Algorithm

针对多架异构无人机在未知环境下协同执行搜索打击任务。考虑无人机和目标资源问题,采用了一种组建联盟方式来完成打击任务,建立了组建联盟的多目标优化模型,并提出了一种并行带精英策略非支配排序的遗传算法(NSGA-Ⅱ)求解模型。通过具体的仿真验证了模型的合理性,分析了不同情况下的算法运行速度,并与传统方法进行对比,证明了并行NSGA-Ⅱ具有很强的实时性,且提高了任务的完成效率。

To deal with the problem of cooperation of multiple heterogeneous UAVs for target searching and attacking in unknown environment,and with consideration of the resources of the UAVs and the targets,a method of coalition formation was used to complete the task. A multi-objective optimization model was established,and a parallel Non-dominated Sorting Genetic Algorithm（ NSGA-Ⅱ） was proposed to solve the problem. A simulation was carried out and an analysis was made to the running speed of the algorithm,which was compared with the traditional methods. The simulation results verified the rationality of the model,and showed that the parallel NSGA-Ⅱ has a strong real-time performance and improves the efficiency of task performing.