基于BPSO的联合火力打击武器目标分配优化  

Joint Fire Strike Weapon Target Assignment Optimization Based on BPSO

作　　者：刘学 王俊[2] 张伟 张跃飞 Liu Xue;Wang Jun;Zhang Wei;Zhang Yuefei(Brigade of Graduate Student,Air Force Command College,Beijing 100097,China;Department of Operation Command,Air Force Command College,Beijing 100097,China)

机构地区：[1]空军指挥学院研究生大队,北京100097 [2]空军指挥学院作战指挥系,北京100097

出　　处：《兵工自动化》2025年第3期1-3,共3页Ordnance Industry Automation

基　　金：全军军事类研究生资助课题(JY2022C167)。

摘　　要：针对联合火力打击作战筹划的核心内容,对联合火力打击武器—目标分配(weapon-target assignment,WTA)优化问题进行研究。综合考虑武器平台的毁伤能力、数量以及目标的特性等约束性因素,以最大化打击预期价值收益和最小化打击成本费用为优化目标,建立武器—目标分配多目标约束优化模型;采用离散二进制粒子群(binary particle swarm optimization,BPSO)算法进行求解,得到较为理想的联合火力打击武器—目标分配优化方案。结果表明,该研究可为构建更合理的武器—目标分配优化模型及设计更高效的智能算法提供参考。Weapon-target assignment(WTA)is the core content of joint fire strike operational planning,so the optimization of weapon-target distribution of joint fire strike is studied.A multi-objective constrained optimization model of weapon-target allocation is established,in which the constraint factors such as the damage capability and number of weapon platforms and the characteristics of targets are comprehensively considered,and the maximization of the expected strike value income and the minimization of the strike cost are taken as the optimization objectives;The discrete binary particle swarm optimization(BPSO)algorithm is used to solve the problem,and the ideal optimization scheme of weapon-target assignment for joint fire strike is obtained.The results show that the research can provide a reference for building a more reasonable optimization model of weapon-target assignment and designing a more efficient intelligent algorithm.

关 键 词：离散二进制粒子群 联合火力打击 武器目标分配 仿真实验 

分 类 号：TJ04[兵器科学与技术—兵器发射理论与技术]