Genetic algorithm parameter tuning based on simulated annealing

Through analysis of the essence of genetic algorithm parameter tuning and weigh the pros and cons of various meta-heuristics, a genetic algorithm parameters optimization scheme based on simulated annealing was proposed in this paper.The purpose of this paper is to choose parameters which having high quality for genetic algorithm, to improve the performance of genetic algorithm instance. In the experimental section, comprehensive test method was selected as control group. It verified that if using the parameters getting from this algorithm, genetic algorithm instance can fast convergence and can get high quality solutions. The ability of genetic algorithm solving optimization problems can be greatly improved by the algorithm proposed in this paper.