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Soft Computing
Erschienen in: Soft Computing 4/2014

01.04.2014 | Focus

Particle swarm optimization algorithm driven by multichaotic number generator

verfasst von: Michal Pluhacek, Roman Senkerik, Ivan Zelinka

Erschienen in: Soft Computing | Ausgabe 4/2014

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Abstract

In this paper, the utilization of different chaotic systems as pseudo-random number generators (PRNGs) for velocity calculation in the PSO algorithm are proposed. Two chaos-based PRNGs are used alternately within one run of the PSO algorithm and dynamically switched over when a certain criterion is met. By using this unique technique, it is possible to improve the performance of PSO algorithm as it is demonstrated on different benchmark functions.
Vorheriger Artikel Behaviour of pseudo-random and chaotic sources of stochasticity in nature-inspired optimization methods
Nächster Artikel On the influence of different number generators on results of the symbolic regression

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Metadaten
Titel
Particle swarm optimization algorithm driven by multichaotic number generator
verfasst von
Michal Pluhacek
Roman Senkerik
Ivan Zelinka
Publikationsdatum
01.04.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 4/2014
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-014-1222-z

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