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Gender-Hierarchy Particle Swarm Optimizer Based on Punishment

  • Jiaquan Gao
  • Hao Li
  • Luoke Hu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6145)

Abstract

The paper presents a novel particle swarm optimizer (PSO), called gender-hierarchy particle swarm optimizer based on punishment (GH-PSO). In the proposed algorithm, the social part and recognition part of PSO both are modified in order to accelerate the convergence and improve the accuracy of the optimal solution. Especially, a novel recognition approach, called general recognition, is presented to furthermore improve the performance of PSO. Experimental results show that the proposed algorithm shows better behaviors as compared to the standard PSO, tribes-based PSO and GH-PSO with tribes.

Keywords

gender hierarchy recognition particle swarm optimizer 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jiaquan Gao
    • 1
  • Hao Li
    • 1
  • Luoke Hu
    • 2
  1. 1.Zhijiang CollegeZhejiang University of TechnologyHangzhouChina
  2. 2.College of Mechanical EngineeringZhejiang University of TechnologyHangzhouChina

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