Performance Analysis of Adaptive Genetic Algorithms with Fuzzy Logic and Heuristics

作     者：Yun, Youngsu Gen, Mitsuo 

作者机构：School of Automotive Industrial & Mechanical Engineering Daegu University Kyungbook South Korea Graduate School of Information Production & Systems Waseda University Kitakyushu Japan 

出 版 物：《Fuzzy Optimization and Decision Making》 (模糊最优化与决策)

年 卷 期：2003年第2卷第2期

页      面：161-175页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

摘      要：In this paper, we propose some genetic algorithms with adaptive abilities and compare with them. Crossover and mutation operators of genetic algorithms are used for constructing the adaptive abilities. All together four adaptive genetic algorithms are suggested: one uses a fuzzy logic controller improved in this paper and others employ several heuristics used in conventional studies. These algorithms can regulate the rates of crossover and mutation operators during their search process. All the algorithms are tested and analyzed in numerical examples. Finally, a best genetic algorithm is recommended.