Detail publikačního výsledku

Multivariate Gaussian Copula in Estimation of Distribution Algorithm with Model Migration

HYRŠ, M.; SCHWARZ, J.

Originální název

Multivariate Gaussian Copula in Estimation of Distribution Algorithm with Model Migration

Anglický název

Multivariate Gaussian Copula in Estimation of Distribution Algorithm with Model Migration

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The paper presents a new concept of an island-based model of Estimation of Distribution Algorithms (EDAs) with a bidirectional topology in the field of numerical optimization in continuous domain.
The traditional migration of individuals is replaced by the probability model migration.
Instead of a classical joint probability distribution model, the multivariate Gaussian copula is used which must be specified by correlation coefficients and parameters of a univariate marginal distributions.
The idea of the proposed Gaussian Copula EDA algorithm with model migration (GC-mEDA) is to modify the parameters of a resident model respective to each island by the immigrant model of the neighbour island.
The performance of the proposed algorithm is tested over a group of five well-known benchmarks.

Anglický abstrakt

The paper presents a new concept of an island-based model of Estimation of Distribution Algorithms (EDAs) with a bidirectional topology in the field of numerical optimization in continuous domain.
The traditional migration of individuals is replaced by the probability model migration.
Instead of a classical joint probability distribution model, the multivariate Gaussian copula is used which must be specified by correlation coefficients and parameters of a univariate marginal distributions.
The idea of the proposed Gaussian Copula EDA algorithm with model migration (GC-mEDA) is to modify the parameters of a resident model respective to each island by the immigrant model of the neighbour island.
The performance of the proposed algorithm is tested over a group of five well-known benchmarks.

Klíčová slova

Estimation of distribution algorithms, Copula Theory, Sklar's theorem, multivariate Gaussian copula, island-based model, model migration, optimization problems. 

Klíčová slova v angličtině

Estimation of distribution algorithms, Copula Theory, Sklar's theorem, multivariate Gaussian copula, island-based model, model migration, optimization problems. 

Autoři

HYRŠ, M.; SCHWARZ, J.

Rok RIV

2015

Vydáno

11.12.2014

Nakladatel

Institute of Electrical and Electronics Engineers

Místo

Piscataway

ISBN

978-1-4799-4492-7

Kniha

2014 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Proceedings

Strany od

114

Strany do

119

Strany počet

6

BibTex

@inproceedings{BUT111681,
  author="Martin {Hyrš} and Josef {Schwarz}",
  title="Multivariate Gaussian Copula in Estimation of Distribution Algorithm with Model Migration",
  booktitle="2014 IEEE Symposium on Foundations of Computational  Intelligence (FOCI) Proceedings",
  year="2014",
  pages="114--119",
  publisher="Institute of Electrical and Electronics Engineers",
  address="Piscataway",
  doi="10.1109/FOCI.2014.7007815",
  isbn="978-1-4799-4492-7"
}