基于多层编码遗传算法的舰载机群兵力行动规划方法

doi:10.12305/j.issn.1001-506X.2025.02.22

摘要/Abstract

摘要：

多机种舰载机协同作战是发挥航母编队作战能力的关键问题, 因此科学设计舰载机群兵力行动规划和相关资源的分配对于提高航母作战效能而言具有重要意义。首先, 基于舰载机对陆突击作战任务的特点和兵力组成、弹药挂载等约束条件, 围绕兵力行动规划一体化作战调度问题展开研究; 然后, 针对舰载机群出动离场、航迹规划、空中加油、协同作战、着舰回收等关键阶段进行一体化作战调度建模, 并引入启发式-多层编码的遗传算法, 对各关键阶段之间的耦合关系进行解耦处理; 再次, 通过使用改进凸优化算法对案例中舰载机航行路径进行航迹规划并计算出航行时间, 将该时间作为兵力行动规划和调度输入数据使用; 最后, 基于案例仿真进行14机、18机、20机、24机的舰载机群兵力行动规划调度的时序规划和相关资源的科学分配, 验证所设计模型和算法的可行性和鲁棒性。

关键词: 启发式-多层编码, 遗传算法, 凸优化, 一体化作战调度

Abstract:

The cooperative operation of multiple types of carrier aircraft is the key challenge to develop the combat capability of carrier aircraft formation. Therefore, the scientific design of carrier aircraft group force action planning and the allocation of related resources are of great significance to improve the combat efficiency of carrier aircraft. Firstly, based on the characteristics of the carrier aircraft's land assault combat mission, force composition, ammunition loading and other constraints, and the integrated operational scheduling of force action planning is studied. Secondly, the integrated combat scheduling model is carried out for the key stages of carrier aircraft group departure, track planning, air refueling, cooperative combat, landing aircraft recovery, etc., and the heuristic-multi-layer coding genetic algorithm is introduced to decoupage the coupling relationship between each key stage. Thirdly, the improved convex optimization algorithm is used to plan the trajectory path of the carrier aircraft in the case and to calculate the flight time, which is used as the input data for force action planning and scheduling. Finally, based on the case simulation, the time series planning and the scientific allocation of related resources for the force action planning and scheduling of 14, 18, 20 and 24 carrier aircrafts are carried out respectively, and the feasibility and robustness of the designed model and proposed algorithm are verified.

Key words: heuristic-multi-layer coding, genetic algorithm, convex optimization, integrated combat scheduling

中图分类号:

吴浩南, 韩维, 潘子双, 郭放, 苏析超. 基于多层编码遗传算法的舰载机群兵力行动规划方法[J]. 系统工程与电子技术, 2025, 47(2): 555-567.

Haonan WU, Wei HAN, Zishuang PAN, Fang GUO, Xichao SU. Multi-layer coding genetic algorithm-based approach to force action planning for carrier aircraft fleets[J]. Systems Engineering and Electronics, 2025, 47(2): 555-567.

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变量	变量含义
I	参与调度的舰载机集合
J_ij	第i架舰载机属于第j个编组
Sw_ij	第i架舰载机第j个任务开始的时间
Ew_ij	第i架舰载机第j个任务结束的时间
Sz_ij	第i架舰载机第j个任务阵地转移开始的时间
Ez_ij	第i架舰载机第j个任务阵地转移结束的时间
U_e	舰载机出动离场的任务集合
U_d	舰载机着舰回收的任务集合
U_s	舰载机编队任务的任务集合
dw_ij	第i架舰载机在第j阶段任务执行所用时间
O_ij	第i架舰载机在第j阶段的任务集
P_ij	第i架舰载机第j阶段任务所在阵地
r_ij	第i架舰载机在第j阶段的空中加油任务中所需要的燃油的数量
R_k	一个加油编组中加燃油机供应的燃油的上限
M	所在航母单波保障舰载机数量上限

编号	作战任务内容	单架舰载机所需弹药
O_s1	出动离场	-
O_s2	集结编队	-
O₁₁	探测红方防空巡逻区	-
O₂₁	与红方舰载机进行空战	2枚空空导弹
O₂₂	对干扰机进行空中护航	-
O₂₃, O₃₃	任务后空中加油	-
O₃₁	对红方2号目标电子干扰	2枚反辐射弹
O₃₂	对红方6号目标电子干扰	2枚反辐射弹
O₄₁	提供任务前空中加油	-
O₅₁, O₆₁, O₇₁	任务前空中加油	-
O₅₂	摧毁红方3号目标	2枚空地导弹
O₅₃	对红方4号目标实施电子干扰	2枚反辐射弹
O₅₄	对红方5号目标实施电子干扰	2枚反辐射弹
O₆₂	对红方1号目标实施近距打击	2枚航空炸弹
O₇₂	对红方1号目标实施远距打击	2枚空地导弹
O₈₁	提供任务后空中加油	-
O_E	着舰回收	-

编组	14机编组飞机数目	18机编组飞机数目	20机编组飞机数目	24机编组飞机数目
预警探测	1	1	1	2
压制防空	2	3	3	4
空中护航	2	2	3	3
电子干扰	1	2	3	3
低空突防	2	3	3	4
远程打击	2	3	3	4
空中加油	4	4	4	4

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