Multiobjective particle swarm optimization using fuzzy logic

Authors:
Hossein Yazdani;Halina Kwasnicka;Daniel Ortiz-Arroyo
Affiliations:
Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland;Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland;Electronics Department, Computational Intelligence and Security Laboratory, Aalborg University, Denmark
Venue:
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
Year:
2011

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Abstract

The paper presents FMOPSO a multiobjective optimization method that uses a Particle Swarm Optimization algorithm enhanced with a Fuzzy Logic-based controller. Our implementation makes use of a number of fuzzy rules as well as dynamic membership functions to evaluate search spaces at each iteration. The method works based on Pareto dominance and was tested using standard benchmark data sets. Our results show that the proposed method is competitive with other approaches reported in the literature.