Publication Details
Multivariate Gaussian Copula in Estimation of Distribution Algorithm with Model Migration
Schwarz Josef, doc. Ing., CSc. (CM-SFE)
Estimation of distribution algorithms, Copula Theory, Sklar's theorem, multivariate Gaussian copula, island-based model, model migration, optimization problems.
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.
@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"
}