分布式遗传模拟退火算法的火力打击目标分配优化

根据火力打击规则,建立了多目标函数的目标分配模型,提出了分布式遗传模拟退火算法对模型进行求解。分布式遗传模拟退火算法基于经典遗传算法进行改进:将单目标串行搜索方式变成多目标分布式搜索方式,适用于多目标寻优问题求解;采用保留最优个体和轮盘赌相结合的方式进行个体选择,在交叉算子中引入模拟退火算法,使用自适应变异概率,较好地保持算法广度和深度搜索平衡。最后,通过仿真实验验证了算法的有效性和可靠性。

Optimization for Target Assignment in Fire Strike Based on Distributed Genetic Simulated Annealing Algorithm

According to the rules of fire strike,a target assignment model is presented,and a Distributed Genetic Simulated Annealing algorithm (DGSA)is applied to resolve this model. DGSA is improved based on classic Genetic Algorithm (GA)as below:the single object serial-searched mode is changed to multiple objects distributed-searched mode,which is fitter for resolving multiobjective optimization; in order to keep a better balance between exploration and exploitation of algorithm,a method by coupling best one preservation and roulette wheel is established for individual selection,and simulated annealing algorithm is combined into crossover operation,and self -adaptive mutation probability is applied. Finally,the efficiency and reliability of DGSA is verified by simulation experiment.