An effective particle swarm optimization for global optimization

Mahdiyeh Eslami, Hussain Shareef, Mohammad Khajehzadeh, Azah Mohamed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, a novel chaotic particle swarm optimization with nonlinear time varying acceleration coefficient is introduced. The proposed modified particle swarm optimization algorithm (MPSO) greatly elevates global and local search abilities and overcomes the premature convergence of the original algorithm. This study aims to investigate the performance of the new algorithm, as an effective global optimization method, on a suite of some well-known benchmark functions and provides comparisons with the standard version of the algorithm. The simulated results illustrate that the proposed MPSO has the potential to converge faster, while improving the quality of solution. Experimental results confirm superior performance of the new method compared with standard PSO.

Original languageEnglish
Title of host publicationCommunications in Computer and Information Science
Pages267-274
Number of pages8
Volume316 CCIS
DOIs
Publication statusPublished - 2012
Event6th International Symposium on Intelligence Computation and Applications, ISICA 2012 - Wuhan
Duration: 27 Oct 201228 Oct 2012

Publication series

NameCommunications in Computer and Information Science
Volume316 CCIS
ISSN (Print)18650929

Other

Other6th International Symposium on Intelligence Computation and Applications, ISICA 2012
CityWuhan
Period27/10/1228/10/12

Fingerprint

Global optimization
Particle swarm optimization (PSO)

Keywords

  • Chaotic Sequence
  • Global Optimization
  • Nonlinear Acceleration Coefficient
  • Particle Swarm Optimization

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Eslami, M., Shareef, H., Khajehzadeh, M., & Mohamed, A. (2012). An effective particle swarm optimization for global optimization. In Communications in Computer and Information Science (Vol. 316 CCIS, pp. 267-274). (Communications in Computer and Information Science; Vol. 316 CCIS). https://doi.org/10.1007/978-3-642-34289-9_30

An effective particle swarm optimization for global optimization. / Eslami, Mahdiyeh; Shareef, Hussain; Khajehzadeh, Mohammad; Mohamed, Azah.

Communications in Computer and Information Science. Vol. 316 CCIS 2012. p. 267-274 (Communications in Computer and Information Science; Vol. 316 CCIS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Eslami, M, Shareef, H, Khajehzadeh, M & Mohamed, A 2012, An effective particle swarm optimization for global optimization. in Communications in Computer and Information Science. vol. 316 CCIS, Communications in Computer and Information Science, vol. 316 CCIS, pp. 267-274, 6th International Symposium on Intelligence Computation and Applications, ISICA 2012, Wuhan, 27/10/12. https://doi.org/10.1007/978-3-642-34289-9_30
Eslami M, Shareef H, Khajehzadeh M, Mohamed A. An effective particle swarm optimization for global optimization. In Communications in Computer and Information Science. Vol. 316 CCIS. 2012. p. 267-274. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-642-34289-9_30
Eslami, Mahdiyeh ; Shareef, Hussain ; Khajehzadeh, Mohammad ; Mohamed, Azah. / An effective particle swarm optimization for global optimization. Communications in Computer and Information Science. Vol. 316 CCIS 2012. pp. 267-274 (Communications in Computer and Information Science).
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