Parallel BMDA with an Aggregation of Probability Models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F09%3APU82612" target="_blank" >RIV/00216305:26230/09:PU82612 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Parallel BMDA with an Aggregation of Probability Models
Original language description
The paper is focused on the problem of aggregation of probability distribution applicable for parallel Bivariate Marginal Distribution Algorithm (pBMDA). A new approach based on quantitative combination of probabilistic models is presented. Using this concept, the traditional migration of individuals is replaced with a newly proposed technique of probability parameter migration. In the proposed strategy, the adaptive learning of the resident probability model is used. The short theoretical study is completed by an experimental works for the implemented parallel BMDA algorithm (pBMDA). The performance of pBMDA algorithm is evaluated for various problem size (scalability) and interconnection topology. In addition, the comparison with the previously published aBMDA  is presented.
Czech name
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Czech description
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Project
<a href="/en/project/GA102%2F07%2F0850" target="_blank" >GA102/07/0850: Design and hardware implementation of a patent-invention machine</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceeding of 2009 IEEE Congress on Evolutionary Computation
ISBN
978-1-4244-2959-2
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
IEEE Computational Intelligence Society
Place of publication
Trondheim
Event location
Trondheim
Event date
May 18, 2009
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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