摘要
从智能优化视角出发解决联合火力打击任务规划中动态兵力、火力、目标最优化分配问题,设计了信息素遗传算法并将其引入到联合火力打击任务规划问题的求解。信息素遗传算法作为标准遗传算法的改进算法,借鉴了蚁群算法中信息素浓度概念,用信息素浓度控制种群个体变异方向,使用可控变异替代标准遗传算法中的随机变异,使最优个体快速收敛。同时使用熵权法和理想点法将联合火力打击任务规划的众多评估指标融合为可量化对比的综合评分,为任务规划提供评估参考指标。仿真实验结果表明,信息素遗传算法能够有效应用于联合火力打击任务规划问题求解,相较于标准遗传算法具有更高的收敛效率和综合评分。
In order to solve the problem of dynamic allocation of dynamic force,firepower and target in the joint firepower mission planning,the dynamic allocation problem is solved from the perspective of intelligent optimization.The pheromone genetic algorithm is designed and introduced into the joint firepower mission planning problem solving.As an improved algorithm of standard genetic algorithm,pheromone genetic algorithm draws on the concept of pheromone concentration in ant colony algorithm,uses pheromone concentration to control the individual mutation direction,and uses controllable mutation to replace random mutation in standard genetic algorithm to make the optimal individual fast.convergence.At the same time,using the entropy weight method and the ideal point method,the many evaluation indicators of the joint firepower mission planning are integrated into a comprehensive score that can be quantified and compared,and the evaluation reference indicators are provided for the mission planning.The simulation results show that the pheromone genetic algorithm can be effectively applied to the joint fire attack mission planning problem,which has higher convergence efficiency and comprehensive score than the standard genetic algorithm.
作者
邢岩
刘昊
吴世杰
XING Yan;LIU Hao;WU Shijie(School of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110000, China;National Defense University Joint Operations College, Shijiazhuang 050000, China;Liaoning Military Region, Shenyang 110000, China)
出处
《兵器装备工程学报》
CAS
北大核心
2020年第8期169-175,192,共8页
Journal of Ordnance Equipment Engineering
基金
沈阳航空航天大学引进人才科研启动基金(19YB48)
通化师范学院2018年科研基金项目(201837)。
关键词
信息素浓度
遗传算法
蚁群算法
联合作战
火力打击任务规划
智能优化
熵权法
理想点法
pheromone concentration
genetic algorithm
ant colony algorithm
joint operations
firepower mission planning
intelligent optimization
entropy weight method
ideal point method
