混合遗传算法与模拟退火法

Hybrid Genetic Algorithm and Simulated Annealing

论文将适合全局搜索的遗传算法(GA)和适合局部搜索的模拟退火算法(SA)相结合,提出了混合GA-SA计算方法。一方面,算法采用混沌初始化,提高了初始群体的质量;另一方面,算法采用Gray编码以及动态自适应调节交叉概率和变异概率,提高了收敛速度,并有效防止种群早熟现象。实例验证了该算法的可行性和有效性。

This paper puts forward hybrid GA-SA by combining Genetic Algorithm（GA） and Simulated Annealing（SA） together,in which the former is suitable for global searching and the latter is suitable for local searching.In this paper, On the one hand,chaos intialization is adopted in order to improve the quality of initial population.On the other hand, Gray coding and dynamic adaptive probability of crossover and mutation are adopted,which can improve the evolution speed and prevent the population from premature.Four examples show that the hybrid GA-SA is feasible and effective.