期刊名称：Journal of Intelligent Learning Systems and Applications
印刷版ISSN：2150-8402
电子版ISSN：2150-8410
出版年度：2015
卷号：07
期号：02
页码：37-41
DOI：10.4236/jilsa.2015.72004
语种：English
出版社：Scientific Research Publishing
摘要：An iterated function system crossover (IFSX) operation for real-coded genetic algorithms (RCGAs) is presented in this paper. Iterated function system (IFS) is one type of fractals that maintains a similarity characteristic. By introducing the IFS into the crossover operation, the RCGA performs better searching solution with a faster convergence in a set of benchmark test functions.
关键词：Genetic Algorithm; Iterated Function System; Crossover Operation
