Performance Comparison Analysis of Multiple Genetic Algorithms for Function Optimization

The comparision of four kinds of commonly used genetic algorithms(fitness function calibration genetic algorithm,sequential selection genetic algorithm,two-point crossover genetic algorithm and adaptive genetic algorithm) was carried out in solving function optimization problem.And MATLAB was used to simulate the experiment.The simulation shows that better stability is shown in fitness function calibration genetic algorithm,sequential selection genetic algorithm and adaptive genetic algorithm except in two-point crossover genetic algorithm,and the optimal solutions of them are more accurate.Among them,sequential selection genetic algorithm is better than the others.