Research on adaptive genetic algorithm with small population

The effect of mutation operator in simple genetic algorithm and adaptive genetic algorithm is analyzed, and the corresponding study is insufficient. A novel mutation strategy improving the performance of genetic algorithm greatly is introduced, and a new adaptive genetic algorithm with small population is proposed. The new algorithm adopted roulette wheel selection and one-point crossover makes the flexible mutation strategy obtain balance relatively between exploration and exploitation. The proposed method improves the global and local searching ability efficiently, avoids the premature convergence, and obtains the global optimal solution with a small population. The simulation about optimal problems of multimodal function shows the new algorithm is effective.