Particle Swarm Optimization with Flexible Swarm for Unconstrained Optimization

Abstract

Particle Swarm Optimization (PSO) algorithm inspired from behaviour of bird flocking and fish schooling. It is well-known algorithm which has been used in many areas successfully. However it sometimes suffers from premature convergence. In resent year’s researches have been introduced a various approaches to avoid of this problem. This paper presents the particle swarm optimization algorithm with flexible swarm (PSO-FS). The new algorithm was evaluated on 14 functions often used to benchmark the performance of optimization algorithms. PSO-FS algorithm was compared to some other modifications of PSO. The results show that PSO-FS always performed one of the better results.

Authors and Affiliations

Humar Kahramanlı*| Faculty of Technology, Selcuk University Campus,Konya,Turkey. Tel: +90 332 2233330; E-mail:hkahramanli@selcuk.edu.tr, N. Allahverdi| Faculty of Technology, Selcuk University Campus,Konya,Turkey. Tel: +90 332 2233329; E-mail:noval@selcuk.edu.tr

Keywords

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  • EP ID EP737
  • DOI -
  • Views 622
  • Downloads 34

How To Cite

Humar Kahramanlı*, N. Allahverdi (2013). Particle Swarm Optimization with Flexible Swarm for Unconstrained Optimization. International Journal of Intelligent Systems and Applications in Engineering, 1(1), 8-13. https://europub.co.uk/articles/-A-737