Crowding genetic algorithm can obtain multiple optima of multimodal functions, but it has low efficiency, and cannot get a higher precision in limited iterations. In order to obtain all optima of the multimodal function quickly, the crowding genetic algorithm based on logarithmic adaption was presented combined with niche crowding genetic and climbing operators. The algorithm computed the distance values of climbing operators by logarithmic adaption according to the iterations, which made the population maintain genetic diversity in the process. According to the experiments and comparative ana...
