New method of fuzzy-based genetic algorithms

Fuzzy logic is one of the newly adduced self-adaptive strategies,which is applied to dynamically adjust the parameters of genetic algorithms for the purpose of enhancing the performance.A newly fuzzy-based genetic algorithm(FGA) is proposed,which utilizes the evolutionary process and the diversity of the population,to adaptively tune the rates of crossover and mutation with fuzzy logic controller.The results of the experiment show that our FGA performs much better than simple genetic algorithm(SGA),not only in the precision,but also in the searching speed.The proposed FGA ameliorate the premature situation and some other problems existed in the SGA.