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An Improved Particle Swarm Optimization Algorithm for Global Numerical Optimization

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3991)

Abstract

This paper presents an improved particle swarm optimization algorithm (IPSO) for global numerical optimization. The IPSO uses more particles’ information to control the mutation operation. A new adaptive strategy for choosing parameters is also proposed to assure convergence of the IPSO. Meanwhile, we execute the IPSO to solve eight benchmark problems. The results show that the IPSO is superior to some existing methods for finding the best solution, in terms of both solution quality and algorithm robustness.

Keywords

Particle Swarm Optimization Benchmark Function High Quality Solution Particle Swarm Optimization Method Standard Particle Swarm Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bo Zhao
    • 1
  1. 1.Jiangsu Electric Power Research Institute Corporation LimitedNanjingChina

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