Doc. Ing. Jiří Jaroš, Ph.D.

JAROŠ Jiří and SCHWARZ Josef. Parallel BMDA with an Aggregation of Probability Models. In: Proceeding of 2009 IEEE Congress on Evolutionary Computation. Trondheim: IEEE Computational Intelligence Society, 2009, pp. 1683-1690. ISBN 978-1-4244-2959-2.
Publication language:english
Original title:Parallel BMDA with an Aggregation of Probability Models
Title (cs):Paralelní BMDA s Agregací Pravděpodobnostních Modelů
Pages:1683-1690
Proceedings:Proceeding of 2009 IEEE Congress on Evolutionary Computation
Conference:IEEE Congress on Evolutionary Computation
Place:Trondheim, NO
Year:2009
ISBN:978-1-4244-2959-2
Publisher:IEEE Computational Intelligence Society
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Keywords
BMDA, aggregation, probability distributions, migration
Annotation
The paper is focused on the problem of aggregation of probability distribution applicable for parallel Bivariate Marginal Distribution Algorithm (pBMDA). A new approach based 000274803100222on 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.
BibTeX:
@INPROCEEDINGS{
   author = {Ji{\v{r}}{\'{i}} Jaro{\v{s}} and Josef Schwarz},
   title = {Parallel BMDA with an Aggregation of Probability Models},
   pages = {1683--1690},
   booktitle = {Proceeding of 2009 IEEE Congress on Evolutionary Computation},
   year = {2009},
   location = {Trondheim, NO},
   publisher = {IEEE Computational Intelligence Society},
   ISBN = {978-1-4244-2959-2},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=8948}
}

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