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. 212219. ISBN 9789897581571. 
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:  212219 

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:  9789897581571 

Publisher:  SciTePress  Science and Technology Publications 

URL:  [PDF] 

Files:  


Keywords 

Estimation of Distribution Algorithms, Copula Theory, Parallel EDA, Islandbased 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 islandbased version of copulabased EDA with probabilistic model migration (mCEDA) was
tested on a set of wellknown 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 copulabased 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 = {212219},
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 = {9789897581571},
language = {english},
url = {http://www.fit.vutbr.cz/research/view_pub.php.en.iso88592?id=11013}
} 