Performance Analysis of Adaptive Genetic Algorithms with Fuzzy Logic and Heuristics
Performance Analysis of Adaptive Genetic Algorithms with Fuzzy Logic and Heuristics
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DOI：
10.1023/a:1023499201829
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发表时间：
2003-06
影响因子：
4.7
通讯作者：
YoungSu Yun;M. Gen
中科院分区：
文献类型：
--
作者：
YoungSu Yun;M. Gen
在本文中，我们提出了一些具有自适应能力的遗传算法并与它们进行了比较。遗传算法的交叉和变异算子用于构建自适应能力。总共提出了四种自适应遗传算法：一种使用本文改进的模糊逻辑控制器，另一些则采用传统研究中使用的几种启发式算法。这些算法可以在搜索过程中调节交叉和变异算子的速率。所有算法均通过数值算例进行了测试和分析。最后推荐了一种最佳的遗传算法。
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.