ファジィ適応型探索GAの提案とTSP問題への応用(一般講演11)

抄録

In this research,we proposed a method to improve the search capacity of genetic algorithm. The genetic operations of a simple GA are mainly constructed by the crossover and the mutation. The mutation almost works to hold the variety of solutions in the first stage. The crossover almost works to converge solutions in the last stage. The former play a trick mainly in the last stage and the later in the first stage. Therefore, we improved the search capacity of Simple GA by controlling the mutation rate and the selection rate with fuzzy rules. Simulation results of Traveling Salesman Problem are also shown in this paper.