Particle Swarm Optimization: Performance Tuning and Empirical Analysis

  • Millie Pant
  • Radha Thangaraj
  • Ajith Abraham
Part of the Studies in Computational Intelligence book series (SCI, volume 203)

Abstract

This chapter presents some of the recent modified variants of Particle Swarm Optimization (PSO). The main focus is on the design and implementation of the modified PSO based on diversity, Mutation, Crossover and efficient Initialization using different distributions and Low-discrepancy sequences. These algorithms are applied to various benchmark problems including unimodal, multimodal, noisy functions and real life applications in engineering fields. The effectiveness of the algorithms is discussed.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Millie Pant
    • 1
  • Radha Thangaraj
    • 1
  • Ajith Abraham
    • 2
  1. 1.Department of Paper TechnologyIIT RoorkeeIndia
  2. 2.Q2S, Norwegian University of Science and TechnologyNorway

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