Improved Self-Adaptive Genetic Algorithm with Varying Population Size

The size of the population can be critical in many application of genetic algorithm. And the probabilities of crossover and mutation have an effect on the diversity of population and the convergence of algorithm. In this paper we propose an adaptive method for crossover and mutation probabilities, which change with the varying population size. This algorithm could make great progress in searching for the global optimization. The experimental results indicate some merits of the proposed method.