A novel centroid particle swarm optimization algorithm based on two subpopulations

Yongsheng WANG*, Junli LI, Yang LOU

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

Abstract

This paper proposed the concept of centroid in particle swarm optimization which is similar to physical centroid properties of objects. Similarly, we may think of a particle swarm as a discrete system of particles and find the centroid representing the entire population. Usually, it has a more promising position than worse particles among the population. In order to verify the role of centroid which can speed up the convergence rate of the algorithm, and prevent the algorithm from being trapped into a local solution early as far as possible at the same time, A Novel Centroid Particle Swarm Optimization Algorithm Based on Two Subpopulations (CPSO) is proposed. Numerical simulation experiments show that CPSO by testing some benchmark functions is better than Linear Decreasing Weight PSO (LDWPSO) in convergence speed in the same accuracy of solution case.

Original languageEnglish
Title of host publicationApplied Mechanics And Mechanical Engineering
EditorsHonghua TAN
Place of PublicationSwitzerland
PublisherTrans Tech Publications Ltd
Pages929-933
Number of pages5
ISBN (Print)9780878492459
DOIs
Publication statusE-pub ahead of print - 2010
Externally publishedYes
Event2010 International Conference on Applied Mechanics and Mechanical Engineering - Changsha, China
Duration: 8 Sep 20109 Sep 2010

Publication series

NameApplied Mechanics and Materials
PublisherTrans Tech Publications Ltd
Volume29-32
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2010 International Conference on Applied Mechanics and Mechanical Engineering
Abbreviated titleICAMME 2010
Country/TerritoryChina
CityChangsha
Period8/09/109/09/10

Keywords

  • Centroid
  • Convergence speed
  • Particle Swarm Optimization Algorithm
  • Subpopulation

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