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Genetic Algorithm Tuning Based on FuzZy Logic

ZHANG Xiao-lei,ZHAO Pei-qing(BEIJING CSCA TECHNOLOGY Co.,Itd.,Beijing 100080,China)  
In order to avoid the premature convergence and improve the performance of genetic algorithm,two evaluation indexex are proposed in this paper.The fuzzy logic combined with these two evaluation indexes is applied to tune the mutation and crossover probability of genetic algorithm.The experiments on functional optimization indicate that our genetic algorithm can get fast convergence and find better results.
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