多目标函数遗传算法在反恐兵力分配中的应用  

Multi-Objective Function Genetic Algorithm in the Application of the Counter Terrorism Forces Distribution

作　　者：陈鲁巧 巩青歌 CHEN Luqiao;GONG Qingge(Postgraduate Brigade;Department of Information Engineering, Engineering University of PAP, Xi＇an 710086, China)

机构地区：[1]武警工程大学研究生管理大队,西安710086 [2]武警工程大学信息工程系,西安710086

出　　处：《武警工程大学学报》2017年第6期18-22,共5页Journal of Engineering University of the Chinese People＇s Armed Police Force

摘　　要：选取反恐作战过程中三个重要因素“持续战斗时间，人员伤亡率和弹药消耗量”进行建模，寻找最优分配方案，提出了一种基于多目标遗传算法（MOGA）的兵力分配模型，通过遗传算法中的并列选择法，对目标函数进行仿真与综合最优值的求解。结果表明，该算法能快速、高效地得出最优值以及最佳的兵力分配方案，可作为优化分配兵力的科学决策依据。Selects three important factors such as continuous combat time, casualty rate and ammunition consumption in anti-terroris combat to model. In order to find the optimal allocation scheme, we propose a force allocation model based on the multi-objective genetic algorithm （MOGA）, through the parallel selection method in the genetic algorithm. The objective function is simulated and the optimal value is solved. The results show that the proposed algorithm can quickly and efficiently obtain the optimal value and the optimal allocation scheme, and it also can be used a as scientific decision basis for optimal allocation of strength.

关 键 词：多目标函数 遗传算法 反恐 兵力分配 

分 类 号：E847[军事—战术学]