Paper Title:
Particle Swarm Optimization with Team Spirit Inertia Weight
  Abstract

A PSO Algorithm with Team Spirit Inertia weight (TSWPSO) is presented based on the study of the effect of inertia weight on Standard Particle Swarm Optimization (SPSO). Due to the theory of group in organization psychology, swarm is divided into multiple sub-swarms and search is run in a number of different sub-swarms which are parallel performed. Try to find or modify a curve which is compatible with optimized object within many inertia weight decline curves, in order to balance the global and local explorations ability in particle swarm optimization and to avoid the premature convergence problem effectively. The testes by five classical functions show that, TSWPSO has a better performance in both the convergence rate and the precision.

  Info
Periodical
Advanced Materials Research (Volumes 383-390)
Chapter
Chapter 22: Computer-Aided Engineering in Manufacturing
Edited by
Wu Fan
Pages
5744-5750
DOI
10.4028/www.scientific.net/AMR.383-390.5744
Citation
X. Z. Wang, Y. Li, G. H. Cheng, "Particle Swarm Optimization with Team Spirit Inertia Weight", Advanced Materials Research, Vols. 383-390, pp. 5744-5750, 2012
Online since
November 2011
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Price
$32.00
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