Faculty of Information Technology, BUT

Publication Details

Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm with Model Migration

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.
Czech title
Eliptické a Archimedovské kopule v EDA s migrací modelů
Type
conference paper
Language
english
Authors
Hyrš Martin, Ing. (DCSY FIT BUT)
Schwarz Josef, doc. Ing., CSc. (DCSY FIT BUT)
URL
Keywords
Estimation of Distribution Algorithms, Copula Theory, Parallel EDA, Island-based Model, Multivariate
Copula Sampling, Migration of Probabilistic Models.
Abstract
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.
Published
2015
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, Lisbon, PT
ISBN
978-989-758-157-1
Publisher
SciTePress - Science and Technology Publications
Place
Lisbon, PT
BibTeX
@INPROCEEDINGS{FITPUB11013,
   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 = "https://www.fit.vut.cz/research/publication/11013"
}
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