求解电子对抗兵力规划问题的改进型混合遗传算法

An Improved Hybrid Genetic Optimization Algorithm for Electronic Countermeasure Dynamic Force Formation Problem

从现代战争指挥运用角度出发,通过分析电子对抗作战筹划和战斗实施全过程,理清电子对抗在战争中的任务及指挥需求;通过对实际电子对抗作战行动的抽象,充分考虑环境、资源等因素,建立电子对抗兵力规划模型;运用Lanchester信息战模型对电子对抗筹划阶段兵力进行初始化处理,进而提出改进型混合遗传算法,对模型进行求解。通过对实际模型算例进行求解,得到了电子对抗兵力规划结果,表明构设算法的有效性,为指挥员运用电子对抗分队提供了指导性依据。与同类型的3种遗传算法进行对比,表明所构设算法能够快速解决此类问题并且在算法稳定性上有相对的优势。

From the perspective of modern warfare command application,this article analyzes the entire process of electronic countermeasures combat planning and combat implementation to clarify the tasks and command requirements of electronic countermeasures in war. By abstracting the actual electronic countermeasures combat operations,fully considering the environment,resources and other factors,Establishment of dynamic model of electronic countermeasures force. Through the use of Lanchester information warfare model to estimate the force of electronic countermeasures planning stage,and then an improved hybrid genetic algorithm is proposed to solve the model. By solving the actual model calculation example,the electronic warfare force formation plan that can directly guide the combat shows the effectiveness of the algorithm constructed is obtained in this paper,and provides a guiding basis for the commander to use electronic warfare units,and compares it with three genetic algorithms of the same type. The results show that this paper Constructing algorithms can quickly solve such problems and has a relative advantage in algorithm stability.