【摘要】 随着无人机技术的发展,无人机的应用环境越来越复杂,促进了无人机从单平台向多平台的集群化发展。针对无人机集群并行执行任务时间最短的目标,设计了一种基于任务节点的交叉避免的蚁群算法,将这些结果和Lingo 17精确算法运行的结果进行对比。最后的测试结果显示论文的算法可以取得非常高的准确度的同时运行时间非常小,说明该算法可以有效地求解无人机集群最小化最长路径问题,从而可以解决并行任务执行时间最小的问题。更多还原

【Abstract】 With the development of UAV technology,the application environment of UAV becomes more and more complex,which promotes the development of UAV from single platform to multi platform cluster. Aiming at the shortest parallel execution time of UAV cluster,an ant colony algorithm based on task node crossover avoidance is designed. These results are compared with LINGO 17 algorithm. Finally,the test results show that the algorithm can achieve very high accuracy,while the running time is very small,which shows that the algorithm can effectively solve the shortest path problem of UAV cluster minimization,so it can solve the problem of minimum parallel task execution time.更多还原