Simulationand Adaptive Genetic Algorithm Used in Function Optimization

Genetic algorithms play a very important role in artificial intelligence.Performance of genetic algorithms is dramaticly influenced by algorithmic settings.To improve the research performance of genetic algorithm and avoid its limitation of local optimization,genetic algorithms is studied and it is found that the size of Pc and Pm is related to the fitness of individuals,and the algorithm should always protect the individuals with high fitness in the running process,A new adaptive genetic algorithm is applied to optimize three standard benchmark functions selected in this paper.The comparison between the results of the present algorithm and simulation of simple genetic algorithm shows that the technique has improved the performance of genetic algorithm.