系统仿真学报 ›› 2017, Vol. 29 ›› Issue (10): 2254-2261.doi: 10.16182/j.issn1004731x.joss.201710004

• 仿真建模理论与方法 • 上一篇    下一篇

基于模糊遗传的联合作战目标组合选择方法

李随科, 向建华, 王海军, 张明智, 李义   

  1. 国防大学信息作战与指挥训练教研部,北京 100091
  • 收稿日期:2017-05-17 发布日期:2020-06-04
  • 作者简介:李随科(1984-), 男, 河南卢氏, 博士后, 研究方向为数据分析与决策; 向建华(1969-), 男, 湖北孝感, 硕士, 教授, 研究方向为演习数据与规则。
  • 基金资助:
    国家自然科学基金(71401168)

Target Combination Selection Optimization Method of Joint Operations based on Fuzzy Genetic algorithm

Li Suike, Xiang Jianhua, Wang Haijun, Zhang Mingzhi, Li Yi   

  1. The Department of Information Operation & Command Training, National Defense University, Beijing 100091, China
  • Received:2017-05-17 Published:2020-06-04

摘要: 信息化条件下联合作战目标和火力决策,需要借助智能模型和优化方法,实现多军兵种作战火力的协作与融合。针对联合作战目标决策和火力配置问题,以实现达成总体目标的最大实现和火力的最优发挥为双目标,构建模糊多目标的规划模型。在模型求解算法上,运用可能性理论对模糊数进行转化,将模型转换为确定形式的多目标规划模型,设计多目标遗传算法优化处理,提高算法的效率。并通过实例数据对构建的模型及设计的求解方法进行验证,得出双目标的帕累托最优集

关键词: 联合作战, 目标选择组合, 模糊数, 多目标遗传算法

Abstract: Under the condition of informatization, it is necessary to use intelligent model and optimization method to realize the cooperation and fusion of multi arms combat firepower. Aiming at the problem of target decision-making and firepower allocation in joint operations, the fuzzy multi-objective programming model was constructed to achieve the overall goal of achieving the maximum and the best firepower as a dual goal. In the model solving algorithm, the possibility theory was used to transform the fuzzy number, the model was transformed into the multi-objective programming model in the deterministic form. In order to improve the efficiency of the algorithm, the multi-objective genetic algorithm was optimized. Through the example data, the model and the design method were validated, and the Pareto optimal set of two objectives was obtained.

Key words: joint operation, target selection combination, fuzzy number, multi-objective genetic algorithm

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