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Handling Multi-optimization with Gender-Hierarchy Based Particle Swarm Optimizer

  • Wei Wei
  • Weihui Zhang
  • Yuan Jiang
  • Hao Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7331)

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.

Keywords

Gender Hierarchy Particle Swarm Optimizer Multi-objective Optimization Rectilinear Distance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Wei Wei
    • 1
  • Weihui Zhang
    • 2
  • Yuan Jiang
    • 1
  • Hao Li
    • 2
  1. 1.China Jiliang UniversityHangzhouChina
  2. 2.Department of Computer ScienceZhejiang University of TechnologyHangzhouChina

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