Two-phase genetic algorithm applied in the optimization of multi-modal function

This paper presents a two-phase genetic algorithm (TPGA) based on the multi-parent genetic algorithm (MPGA). Through analysis we find MPGA will lead the population’s evolvement to diversity or convergence according to the population size and the crossover size, so we make it run in different forms during the global and local optimization phases and then forms TPGA. The experiment results show that TPGA is very efficient for the optimization of low-dimension multi-modal functions) usually we can obtain all the global optimal solutions. Foundation item: Supported by the National Natural Science Foundation of China (70071042, 60073043,60133010) Biography: Huang Yu-zhen ( 1977-), female, Master candidate, research direction; evolution computation.