Iterated Function System-Based Crossover Operation for Real-Coded Genetic Algorithm

S. H. Ling

doi:10.4236/jilsa.2015.72004

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Journal of Intelligent Learning Systems ... > Vol.7 No.2, May 2015

Iterated Function System-Based Crossover Operation for Real-Coded Genetic Algorithm ()

S. H. Ling

Centre for Health Technologies, University of Technology, Sydney, Australia.

DOI: 10.4236/jilsa.2015.72004 PDF HTML XML 4,302 Downloads 4,802 Views Citations

Abstract

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.

Keywords

Genetic Algorithm, Iterated Function System, Crossover Operation

Share and Cite:

Ling, S. (2015) Iterated Function System-Based Crossover Operation for Real-Coded Genetic Algorithm. Journal of Intelligent Learning Systems and Applications, 7, 37-41. doi: 10.4236/jilsa.2015.72004.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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