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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 10/2018

12-04-2017 | Original Article

Fuzzy c-means clustering-based mating restriction for multiobjective optimization

Authors: Yi Zhang, Zimu Li, Hu Zhang, Zhen Yu, Tongtong Lu

Published in: International Journal of Machine Learning and Cybernetics | Issue 10/2018

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Abstract

Mating restriction is an important approach to improve the performance of multiobjective evolutionary algorithms (MOEAs). This paper designs a fuzzy c-means clustering-based mating restriction (FMR) scheme, and proposes a fuzzy c-means clustering-based MOEA named as FCMMO. FMR employs a fuzzy c-means clustering algorithm to discover the clustering structure of the solutions in the population. Based on the structure, a specific mating pool is determined for each solution to generate new solutions. Experimental studies show that FCMMO outperforms five state of the art MOEAs on a set of test instances with complicated Pareto front shapes and Pareto set structures, and FMR significantly contributes to the good performance of FCMMO.
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Metadata
Title
Fuzzy c-means clustering-based mating restriction for multiobjective optimization
Authors
Yi Zhang
Zimu Li
Hu Zhang
Zhen Yu
Tongtong Lu
Publication date
12-04-2017
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 10/2018
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-017-0668-6

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