中文摘要：

模糊逻辑是近年来提出的一种自适应调整策略,可以用来动态调整遗传算法的参数,以提高其性能。在此提出一种模糊逻辑遗传算法（FGA）的新模糊控制系统,它根据种群的进化速度和多样性的反馈信息,通过模糊逻辑控制器来对交叉率和变异率进行动态的自适应控制。实验结果表明,提出的FGA相对于简单遗传算法（SGA）,不仅在与实际最优值差值上获得高1~3个数量级的精度,而且还提高了收敛的速度,较好地解决了SGA容易陷入早熟状态、某些函数进化速度慢等问题。

英文摘要：

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.