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A Multi-Objective Particle Swarm Optimizer Based on Diversity

Authors:
Dennis R. C. Silva
Carmelo J. A. Bastos-Filho

Keywords: swarm intelligence; particle swarm optimization; multi-objective optimization

Abstract:
This paper presents a novel multi-objective optimization algorithm based on Particle Swarm Optimization (MOPSO-DFR), which uses a global density estimator mechanism called Diversity Factor (DF) to select the cognitive and the social leaders. MOPSO-DFR also uses DF to update and to prune the external archive, whenever it is necessary. We used well known metrics to evaluate the results generated by our proposal in seven widely used benchmark functions. We also compared our approach to other four multi-objective optimization algorithms called MOPSO-CDR, SMPSO, NSGA-II and SPEA-2. The results showed that MOPSO-DFR outperforms the other approaches in most cases.

Pages: 109 to 114

Copyright: Copyright (c) IARIA, 2013

Publication date: April 21, 2013

Published in: conference

ISSN: 2308-4065

ISBN: 978-1-61208-269-1

Location: Venice, Italy

Dates: from April 21, 2013 to April 26, 2013