Conference paper

HYRŠ Martin and SCHWARZ Josef. Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm with Model Migration. In: Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015). Lisbon: SciTePress - Science and Technology Publications, 2015, pp. 212-219. ISBN 978-989-758-157-1.
Publication language:english
Original title:Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm with Model Migration
Title (cs):Eliptické a Archimedovské kopule v EDA s migrací modelů
Pages:212-219
Proceedings:Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015)
Conference:International Conference on Evolutionary Computation Theory and Applications 2015
Place:Lisbon, PT
Year:2015
ISBN:978-989-758-157-1
Publisher:SciTePress - Science and Technology Publications
URL: [PDF]
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Keywords
Estimation of Distribution Algorithms, Copula Theory, Parallel EDA, Island-based Model, Multivariate
Copula Sampling, Migration of Probabilistic Models.
Annotation
Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that are based on building
and sampling a probability model. Copula theory provides methods that simplify the estimation of a probability
model. An island-based version of copula-based EDA with probabilistic model migration (mCEDA) was
tested on a set of well-known standard optimization benchmarks in the continuous domain. We investigated
two families of copulas - Archimedean and elliptical. Experimental results confirm that this concept of model
migration (mCEDA) yields better convergence as compared with the sequential version (sCEDA) and other
recently published copula-based EDAs.
BibTeX:
@INPROCEEDINGS{
   author = {Martin Hyr{\v{s}} and Josef Schwarz},
   title = {Elliptical and Archimedean Copulas in Estimation of
	Distribution Algorithm with Model Migration},
   pages = {212--219},
   booktitle = {Proceedings of the 7th International Joint Conference on
	Computational Intelligence (IJCCI 2015)},
   year = {2015},
   location = {Lisbon, PT},
   publisher = {SciTePress - Science and Technology Publications},
   ISBN = {978-989-758-157-1},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.en.iso-8859-2?id=11013}
}

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