Handling multi-optimization with gender-hierarchy based particle swarm optimizer

Authors:
Wei Wei;Weihui Zhang;Yuan Jiang;Hao Li
Affiliations:
China Jiliang University, Hangzhou, Zhejiang, China;Department of Computer Science, Zhejiang University of Technology, Hangzhou, Zhejiang, China;China Jiliang University, Hangzhou, Zhejiang, China;Department of Computer Science, Zhejiang University of Technology, Hangzhou, Zhejiang, China
Venue:
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2012

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Abstract

In this study, we present a novel particle swarm optimizer, called Gender-Hierarchy Based Particle Swarm Optimizer (GH-PSO), to handle multi-objective optimization problems. By employing the concepts of gender and hierarchy to particles, both the exploration ability and the exploitation skill are extended. In order to maintain an uniform distribution of non-dominated solutions, a novel proposal, called Rectilinear Distance based Selection and Replacement (RDSR), is also proposed. The proposed algorithm is validated by using several benchmark functions and metrics. The results show that the proposed algorithm outperforms over MOPSO, NSGA-II and PAES-II.