基于对抗进化的联合火力打击任务规划  

Mission Planning for Joint Firepower Operations Based on Intelligence Combat Evolutionary Algorithm

作　　者：刘昊 朱宁 张晓海 LIU Hao;ZHU Ning;ZHANG Xiao-hai(National Defense University,Joint Operation College,Shijiazhuang 050000;Army Engineering University Shijiazhuang Campus,Shijiazhuang 050000,China)

机构地区：[1]国防大学联合作战学院,河北石家庄050000 [2]陆军工程大学石家庄校区,河北石家庄050000

出　　处：《指挥控制与仿真》2019年第5期10-15,共6页Command Control & Simulation

基　　金：国家社科基金课题(16GJ003-051)

摘　　要：针对联合火力打击任务规划评估优化困难的问题,提出一种基于改进遗传算法的对抗进化算法。该算法引入敌我双方的态势图构建出基于OODA循环的作战超网络,模拟自然竞争原理引入敌我双种群,按照自然竞争的优胜劣汰法则设计个体的遗传和变异操作,实现了敌我双方个体在动态对抗中的自我进化,最终得到最优个体。仿真结果表明:该方法获取的最优个体能够有效解决联合火力打击任务规划的评估优化问题。Difficult problems at joint firepower mission planning is about evaluation and optimization,so propose a intelli gence combat evolutionary algorithm based on improved genetic algorithms.This algorithm designed to use battlefield situation map for building OODA loop super network,and simulated superior bad discard in natural world to design genetic and varia tion module for self evolution.Finally,using algorithm can obtain optimal object.The simulations reveal that the method is useful in mission planning for joint firepower operation.

关 键 词：联合火力打击 任务规划 对抗进化 遗传算法 超网络 OODA环 

分 类 号：E843[军事—战术学]