Performance evaluation of the SOMA asynchronously parallel distribution

Kolek, Jan; Vařacha, Pavel; Motýl, Ivo

dc.title	Performance evaluation of the SOMA asynchronously parallel distribution	en
dc.contributor.author	Kolek, Jan
dc.contributor.author	Vařacha, Pavel
dc.contributor.author	Motýl, Ivo
dc.relation.ispartof	International Journal of Mathematics and Computers in Simulation
dc.identifier.issn	1998-0159 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued	2013
utb.relation.volume	7
utb.relation.issue	1
dc.citation.spage	50
dc.citation.epage	58
dc.type	article
dc.language.iso	en
dc.publisher	North Atlantic University Union (NAUN)	en
dc.relation.uri	http://www.naun.org/multimedia/NAUN/mcs/16-639.pdf
dc.subject	Alltoone	en
dc.subject	Asynchronous	en
dc.subject	Evolutionary algorithm	en
dc.subject	Optimization	en
dc.subject	Parallel	en
dc.subject	SOMA	en
dc.description.abstract	Self-Organising Migrating Algorithm (SOMA) is a very effective tool of evolutionary optimization. This paper deals with performed evaluation of asynchronous parallel version of SOMA, based on the strategy AllToOne. The experiment was focused on the dependence of the solution quality (finding the global extreme value or approximating to global extreme value) on the number of used algorithm threads. In total, 10 different test functions were employed. Each function had 100 dimensions to optimize and the optimization was always repeated 100 times for 1,2,3 and 4 threats. Overlay 4000 independent runs of SOMA were rune and statistically evaluated.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1003097
utb.identifier.obdid	43869904
utb.identifier.scopus	2-s2.0-84872126402
utb.source	j-scopus
dc.date.accessioned	2013-02-02T01:12:51Z
dc.date.available	2013-02-02T01:12:51Z
utb.contributor.internalauthor	Kolek, Jan
utb.contributor.internalauthor	Vařacha, Pavel
utb.contributor.internalauthor	Motýl, Ivo
utb.fulltext.affiliation	Jan Kolek, Pavel Varacha and Ivo Motyl J. Kolek is with the Department of Informatics and Artificial Intelligence, Faculty of Applied Informatics, Tomas Bata University in Zlin, nam. T. G. Masaryka 5555, 760 01 Zlin Czech Republic (e-mail:. kolek@fai.utb.cz). P. Varacha is with the Department of Informatics and Artificial Intelligence, Faculty of Applied Informatics, Tomas Bata University in Zlin, nam. T. G. Masaryka 5555, 760 01 Zlin Czech Republic (e-mail: varacha@fai.utb.cz). I. Motyl is with the Department of Informatics and Artificial Intelligence, Faculty of Applied Informatics, Tomas Bata University in Zlin, nam. T. G. Masaryka 5555, 760 01 Zlin Czech Republic (e-mail: motyl@fai.utb.cz).
utb.fulltext.dates	Manuscript received July 30, 2012 Revised version received August 16, 2012
utb.fulltext.sponsorship	This paper is supported by the Internal Grant Agency at TBU in Zlin, project No. IGA/FAI/2012/041 and project No. IGA/FAI/2012/019 and by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089.
utb.fulltext.projects	IGA/FT/2012/041
utb.fulltext.projects	CZ.1.05/2.1.00/03.0090
utb.fulltext.ou	Department of Informatics and Artificial Intelligence