改进遗传算法求解防空作战WTA问题

Extraction of Weapon-Target Assignment in Air Defense with Improved Genetic Algorithm

武器目标分配问题是防空作战指挥控制的核心和关键。针对求解防空作战WTA存在容易早熟和收敛较慢的问题,提出了一种改进遗传算法。引入直觉模糊集理论,定义了WTA问题的目标函数和约束函数的隶属度和非隶属度函数,通过"最小最大"算子构建了直觉模糊WTA问题模型;针对遗传算法中变异概率固定的竞争和子代种群缺乏父代优良个体的问题,采用自适应变异概率和模拟退火Meta-Lamarckian学习策略改进算法,并求解防空作战WTA问题,与其他算法进行仿真比较,结果表明改进遗传算法求解防空作战WTA的有效性。

Weapon-Target Assignment problem is the key of air defense command and control.Aimed at the problems that precocity and slow convergence exist in the WTA in air defense,an improved genetic algorithm is proposed.The membership and non-membership functions are defined for both object and constrain function by importing the theory of intuitional fuzzy sets,and then an intuitional fuzzy WTA model is established on the basis of the ＂min-max＂operator.In the light of constant mutation probability and lack good father individuals in progeny population,a strategy of Meta-Lamarckian learning for simulated annealing and the adaptive mutation is designed to improve genetic algorithm.The method is effective in solving air defense WTA problem compared with the other algorithms.