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  • - SOMA - Self-Organising Migrating Algorithm is a very effective tool of evolutionary optimization. There are many strategies of this algorithm. This paper deals with performed evaluation of asynchronous parallel version of SOMA, based on the strategy AllToOne, which has been created in programming language Java. The first 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. The aim of the second experiment was to determine the time dependence on the number of used threads.
  • - SOMA - Self-Organising Migrating Algorithm is a very effective tool of evolutionary optimization. There are many strategies of this algorithm. This paper deals with performed evaluation of asynchronous parallel version of SOMA, based on the strategy AllToOne, which has been created in programming language Java. The first 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. The aim of the second experiment was to determine the time dependence on the number of used threads. (en)
Title
  • Performance Evaluation of the Self-Organizing Migration Algorithm Parallel Implementation
  • Performance Evaluation of the Self-Organizing Migration Algorithm Parallel Implementation (en)
skos:prefLabel
  • Performance Evaluation of the Self-Organizing Migration Algorithm Parallel Implementation
  • Performance Evaluation of the Self-Organizing Migration Algorithm Parallel Implementation (en)
skos:notation
  • RIV/70883521:28140/12:43868519!RIV13-MSM-28140___
http://linked.open...avai/riv/aktivita
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  • P(ED2.1.00/03.0089), S
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  • 158191
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  • RIV/70883521:28140/12:43868519
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  • SOMA, asynchronous, optimization, evolutionary algorithm, parallel, AllToOne (en)
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  • [721974E0CFFA]
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  • Proceedings of the 16th WSEAS International Conference on Systems
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  • Motýl, Ivo
  • Vařacha, Pavel
  • Kolek, Jan
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issn
  • 1790-5117
number of pages
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  • WSEAS Press (GR)
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  • 978-1-61804-108-1
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  • 28140
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