文章基本信息

标题：Self-adjusting a Genetic Algorithm Using Fuzzy Logic Techniques
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作者：Mario César López-Locés ; Hector Joaquín Fraire-Huacuja ; Rodolfo Pazos Rangel 等
期刊名称：International Journal of Combinatorial Optimization Problems and Informatics
印刷版ISSN：2007-1558
电子版ISSN：2007-1558
出版年度：2017
卷号：8
期号：1
页码：6-11
语种：English
出版社：International Journal of Combinatorial Optimization Problems and Informatics
其他摘要：One of the most important tasks in approximately solving an optimisation problem is to adjust the parameters of the metaheuristic used as a solution method. As the metaheuristics are usually general in purpose, it is necessary to make adjustments to them for each optimisation problem to which they are applied to get high-quality solutions. In this paper, we propose the use of a Type 1 Fuzzy Inference System and a Type 2 Fuzzy Logic Inference System to select the operators of a Genetic Algorithm during execution time to solve a set of ten test functions from the literature. The results of computational experiments show that the fuzzy selection of operators improves the performance of the original GA on nine of the ten test functions with practically the same execution time.
其他关键词：Fuzzy logic; parameter tuning; genetic algorithm