批量航线航段高度分配方法研究
|
摘要
针对航路网中任务航线高度层的最优分配问题计算规模大、算法难以达到性能需求的难题,文章将问题拆解为两步进行研究,先宏观寻找最优局部,再微观寻找局部最优,保证优化效果的同时大大降低了时间开销。文章在研究过程中提出基于遗传算法的主飞高度优选方法,以及基于环境与个体选择自平衡的航段高度优化调整方法,合理分配任务途经各航段飞行高度,充分利用整个航路网中各高度层的流量容量降低空战场交通冲突概率,提高了计划的可执行性。
Aiming at the problem that the optimal allocation problem of the task route level in the route network is large and the algorithm is difficult to meet the performance requirements, this paper disassembles the problem into two steps, firstly looking for the optimal part and then micro-seeking the local optimum. The optimization effect is greatly reduced while the time overhead is greatly reduced. In the research process, the main flight height optimization method based on genetic algorithm and the segment height optimization adjustment method based on environment and individual self-balancing are proposed. The flight height of each route segment is reasonably allocated, and the altitude level of the entire route network is fully utilized. The flow capacity reduces the probability of air battlefield traffic conflicts and increases the enforceability of the plan.
Aiming at the problem that the optimal allocation problem of the task route level in the route network is large and the algorithm is difficult to meet the performance requirements, this paper disassembles the problem into two steps, firstly looking for the optimal part and then micro-seeking the local optimum. The optimization effect is greatly reduced while the time overhead is greatly reduced. In the research process, the main flight height optimization method based on genetic algorithm and the segment height optimization adjustment method based on environment and individual self-balancing are proposed. The flight height of each route segment is reasonably allocated, and the altitude level of the entire route network is fully utilized. The flow capacity reduces the probability of air battlefield traffic conflicts and increases the enforceability of the plan.
引文
[1] 陈榕.基于改进Dijkstra矩阵算法的多机突击航路规划[J].海军大连舰艇学院学报,2012,35(02):30-32.
[2] 朱涛.基于航路网的批量航线自动规划方法研究[J].信息化研究,2018(05):23-25.
[3] 孙勇成.复杂战场环境空中加油空域规划[J].指挥信息系统与技术,2018,09(03):62-63.
[4] 周昕.遗传算法理论及技术研究综述[J].计算机与信息技术,2010(04):37-39,43.
[5] 梁宇宏.对遗传算法的轮盘赌选择方式的改进[J].信息技术,2009(12):127-129.
[6] 王日凤.启发式搜索策略应用研究及认知系统仿真[J].计算机工程与设计,2011(12):4172-4177.
[2] 朱涛.基于航路网的批量航线自动规划方法研究[J].信息化研究,2018(05):23-25.
[3] 孙勇成.复杂战场环境空中加油空域规划[J].指挥信息系统与技术,2018,09(03):62-63.
[4] 周昕.遗传算法理论及技术研究综述[J].计算机与信息技术,2010(04):37-39,43.
[5] 梁宇宏.对遗传算法的轮盘赌选择方式的改进[J].信息技术,2009(12):127-129.
[6] 王日凤.启发式搜索策略应用研究及认知系统仿真[J].计算机工程与设计,2011(12):4172-4177.