article

Center particle swarm optimization

Authors:

Jiang LuAuthors Info & Claims

Neurocomputing, Volume 70, Issue 4-6

Pages 672 - 679

Published: 01 January 2007 Publication History

Abstract

Center particle swarm optimization algorithm (CenterPSO) is proposed where a center particle is incorporated into linearly decreasing weight particle swarm optimization (LDWPSO). Unlike other ordinary particles in LDWPSO, the center particle has no explicit velocity, and is set to the center of the swarm at every iteration. Other aspects of the center particle are the same as that of the ordinary particle, such as fitness evaluation and competition for the best particle of the swarm. Because the center of the swarm is a promising position, the center particle generally gets good fitness value. More importantly, due to frequent appearance as the best particle of swarm, it often attracts other particles and guides the search direction of the whole swarm. CenterPSO and LDWPSO are extensively compared on three well-known benchmark functions with 10, 20, 30 dimensions. Experimental results show that CenterPSO achieves not only better solutions but also faster convergence. Furthermore, CenterPSO and LDWPSO are compared as neural network training algorithms. The results show that CenterPSO achieves better performance than LDWPSO.

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Cited By

Jamous RALRahhal HEl-Darieby M(2021)A New ANN-Particle Swarm Optimization with Center of Gravity (ANN-PSOCoG) Prediction Model for the Stock Market under the Effect of COVID-19Scientific Programming10.1155/2021/66561502021Online publication date: 1-Jan-2021
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El Afia AAoun OGarcia S(2019)Adaptive cooperation of multi-swarm particle swarm optimizer-based hidden Markov modelProgress in Artificial Intelligence10.1007/s13748-019-00183-18:4(441-452)Online publication date: 1-Dec-2019
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Kushwaha NPant M(2019)Modified particle swarm optimization for multimodal functions and its applicationMultimedia Tools and Applications10.1007/s11042-018-6324-778:17(23917-23947)Online publication date: 1-Sep-2019
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Center particle swarm optimization

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Published In

cover image Neurocomputing

Neurocomputing Volume 70, Issue 4-6

January, 2007

494 pages

ISSN:0925-2312

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2006.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 January 2007

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Cited By

Jamous RALRahhal HEl-Darieby M(2021)A New ANN-Particle Swarm Optimization with Center of Gravity (ANN-PSOCoG) Prediction Model for the Stock Market under the Effect of COVID-19Scientific Programming10.1155/2021/66561502021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6656150
El Afia AAoun OGarcia S(2019)Adaptive cooperation of multi-swarm particle swarm optimizer-based hidden Markov modelProgress in Artificial Intelligence10.1007/s13748-019-00183-18:4(441-452)Online publication date: 1-Dec-2019
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Li NWang WJames Hsu C(2015)Hybrid particle swarm optimization incorporating fuzzy reasoning and weighted particleNeurocomputing10.1016/j.neucom.2015.04.045167:C(488-501)Online publication date: 1-Nov-2015
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