模拟退火自适应大变异遗传算法及其应用

Genetic Algorithm Based on Adaptive Big Mutation Rate and Simulated Annealing and Its Application

为了克服遗传算法易陷入局部最优或早熟问题,提出了一种模拟退火大变异遗传算法,采用了大比例优秀个体保护策略,以保证算法的收敛性。应用该算法求解旅行商问题的仿真实验证明了它能较快地收敛到最优解或准最优解。

To overcome premature or local-best solution, an adaptive big mutation rate algorithm based on simulated annealing, which copies big proportion of the fittest and also melts the theory of simulated annealing algorithm to assure its astringency, is put forward. The simulation to traveling salesman problem proves that the algorithm can rapidly get the best or second best solution.