Convergence Analysis of Particle Swarm Optimizer and Its Improved Algorithm Based on Velocity Differential Evolution
Joint Authors
Luo, Wenguang
Ye, Hongtao
Li, Zhenqiang
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-08-28
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
This paper presents an analysis of the relationship of particle velocity and convergence of the particle swarm optimization.
Its premature convergence is due to the decrease of particle velocity in search space that leads to a total implosion and ultimately fitness stagnation of the swarm.
An improved algorithm which introduces a velocity differential evolution (DE) strategy for the hierarchical particle swarm optimization (H-PSO) is proposed to improve its performance.
The DE is employed to regulate the particle velocity rather than the traditional particle position in case that the optimal result has not improved after several iterations.
The benchmark functions will be illustrated to demonstrate the effectiveness of the proposed method.
American Psychological Association (APA)
Ye, Hongtao& Luo, Wenguang& Li, Zhenqiang. 2013. Convergence Analysis of Particle Swarm Optimizer and Its Improved Algorithm Based on Velocity Differential Evolution. Computational Intelligence and Neuroscience،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-467816
Modern Language Association (MLA)
Ye, Hongtao…[et al.]. Convergence Analysis of Particle Swarm Optimizer and Its Improved Algorithm Based on Velocity Differential Evolution. Computational Intelligence and Neuroscience No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-467816
American Medical Association (AMA)
Ye, Hongtao& Luo, Wenguang& Li, Zhenqiang. Convergence Analysis of Particle Swarm Optimizer and Its Improved Algorithm Based on Velocity Differential Evolution. Computational Intelligence and Neuroscience. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-467816
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-467816