An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization
Joint Authors
Yang, Zhen-Lun
Wu, Angus
Min, Hua-Qing
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
An improved quantum-behaved particle swarm optimization with elitist breeding (EB-QPSO) for unconstrained optimization is presented and empirically studied in this paper.
In EB-QPSO, the novel elitist breeding strategy acts on the elitists of the swarm to escape from the likely local optima and guide the swarm to perform more efficient search.
During the iterative optimization process of EB-QPSO, when criteria met, the personal best of each particle and the global best of the swarm are used to generate new diverse individuals through the transposon operators.
The new generated individuals with better fitness are selected to be the new personal best particles and global best particle to guide the swarm for further solution exploration.
A comprehensive simulation study is conducted on a set of twelve benchmark functions.
Compared with five state-of-the-art quantum-behaved particle swarm optimization algorithms, the proposed EB-QPSO performs more competitively in all of the benchmark functions in terms of better global search capability and faster convergence rate.
American Psychological Association (APA)
Yang, Zhen-Lun& Wu, Angus& Min, Hua-Qing. 2015. An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057682
Modern Language Association (MLA)
Yang, Zhen-Lun…[et al.]. An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1057682
American Medical Association (AMA)
Yang, Zhen-Lun& Wu, Angus& Min, Hua-Qing. An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057682
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057682