考虑复杂环境的多机物资投送任务规划OACSTPCD
Mission planning for multi-aircraft material delivery considering complex environments
针对运输机物资投送的任务分配以及路径规划问题,重点考虑了由恶意干扰导致的运输机损耗以及投送时效性两个复杂性因素,建立了包含运输机损失、总里程数以及未按时受补率三方面的待优化目标函数.同时提出了基于"任务合并"和"饱和补给"等先验知识的优化思路,实现了改进的遗传算法.仿真结果表明,采用融合先验知识的改进遗传算法,改善了因搜索空间过大而导致的优化过程收敛缓慢问题,提升了模型的解算速度和优化效果.
This paper focuses on the task allocation and path planning problem for aircraft material delivery,considering two complexity factors:aircraft loss caused by malicious interference and delivery timeliness.It establishes an objective function to be optimized,which includes aircraft loss,total mileage,and untimely supply rate.Meanwhile,it proposes an optimization approach based on prior knowledge such as "task merging" and "saturation supply",and implements an im-proved genetic algorithm.Simulation results show that the improved genetic algorithm with fused prior knowledge addresses the slow convergence problem caused by a large search space,improving the solution speed and optimization effect of the model.
张雷;安靖;陈亮
国防大学联合作战学院,北京 100091||国防大学联合勤务学院,北京 100858国防大学联合勤务学院,北京 100858军事交通学院汽车士官学校,安徽 蚌埠 233011
多运输机战场物资补给路径规划任务分配遗传算法
multi-aircraftbattlefield material supplypath planningtask allocationgenetic algorithm
《指挥控制与仿真》 2024 (005)
21-28 / 8
全军军事类研究生资助课题
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