Performance Analysis of Adaptive Genetic Algorithms with Fuzzy Logic and Heuristics

被引：70

作者：

Youngsu Yun

Mitsuo Gen

机构：

[1] Daegu University,School of Automotive, Industrial & Mechanical Engineering

[2] Waseda University,Graduate School of Information, Production & Systems

来源：

Fuzzy Optimization and Decision Making | 2003年 / 2卷 / 2期

关键词：

adaptive genetic algorithms; adaptive abilities; fuzzy logic controller;

D O I：

10.1023/A:1023499201829

中图分类号：

学科分类号：

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.

引用

页码：161 / 175

页数：14

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