Multiple choice strategy - A novel approach for particle swarm optimization - Preliminary study

Pluháček, Michal; Šenkeřík, Roman; Zelinka, Ivan

Title:

Author:

Pluháček, Michal; Šenkeřík, Roman; Zelinka, Ivan

Document type:

Conference paper (English)

Source document:

Artificial Intelligence and Soft Computing 2014, Part II. 2013, vol. 7895 LNAI, issue PART 2, p. 36-45

ISSN:

0302-9743 (Sherpa/RoMEO, JCR)

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ISBN:

978-3-642-38609-1

DOI:

https://doi.org/10.1007/978-3-642-38610-7_4

Abstract:

In this paper, a new promising strategy for PSO algorithm is proposed and described. This strategy presents alternative way of assigning new velocity to each particle in population. This new multiple choice particle swarm optimization (MC-PSO) algorithm is tested on four different test functions and the promising results of this alternative strategy are compared with the classic method.

Full text:

https://link.springer.com/chapter/10.1007/978-3-642-38610-7_4

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Citace článku v konferenčním sborníku:
PLUHÁČEK, Michal, Roman ŠENKEŘÍK a Ivan ZELINKA. Multiple choice strategy - A novel approach for particle swarm optimization - Preliminary study. In: Artificial Intelligence and Soft Computing 2014, Part II [online]. Zakopane: Springer-Verlag Berlin, 2013, s. 36-45. [cit. 2024-04-19]. ISSN 0302-9743. Dostupné z: https://link.springer.com/chapter/10.1007/978-3-642-38610-7_4.

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