Improved Dual Population Genetic Algorithm

In this paper,a new genetic algorithm with two populations is proposed.Our dual population genetic algorithm(DPGA) composes of two subpopulation that constitute of same size individuals.The subpopulations have different characteristics,such as crossover probability,mutation operator and reproduction.In one subpopulation,the parents with higher similarity are cross with higher rate;mutate with general mutation operator;the new individual replace the worst individual of the old population.So that,the new algorithm can obtains good exploitation ability.In the other subpopulation,the parents with smaller similarity are cross with higher rate;mutate with big mutation operator;the new individual replace the most similar individual of the old population.So that,the new algorithm can gets good exploration ability.The performance of our DPGA is compare to that of a single population genetic algorithm(SPGA) and Multi-population genetic algorithm with two populations(2PMGA).The experimental results show that the proposed method outperforms SPGA and 2PMGA.