Publication detail

Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm

HYRŠ, M. SCHWARZ, J.

Original Title

Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm

Type

conference paper

Language

English

Original Abstract

Estimation of distribution algorithm (EDA) is a variant of evolution algorithms, which is based on construction and sampling of probability model. Nowadays the copula theory is often utilized for the probability model estimation to simplify this process. We made comparison of two classes of copulas - elliptical and Archimedean ones - for the set of standard optimization benchmarks. The experimental results con firm our assumption that the elliptical copulas outperform the Archimedean ones namely in the case of the complex optimization problems.

Keywords

Estimation of distribution algorithms, copula theory, multivariate copula sampling, Clayton copula, Gumbel copula, Frank copula, Gaussian copula, Student t-copula

Authors

HYRŠ, M.; SCHWARZ, J.

RIV year

2015

Released

25. 6. 2015

Publisher

Faculty of Mechanical Engineering BUT

Location

Brno

ISBN

978-80-214-4984-8

Book

MENDEL 2015 21st International Conference on Soft Computing

Pages from

19

Pages to

26

Pages count

8

URL

https://www.fit.vut.cz/research/publication/11012/

BibTex

@inproceedings{BUT119926,
  author="Martin {Hyrš} and Josef {Schwarz}",
  title="Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm",
  booktitle="MENDEL 2015 21st International Conference on Soft Computing",
  year="2015",
  pages="19--26",
  publisher="Faculty of Mechanical Engineering BUT",
  address="Brno",
  isbn="978-80-214-4984-8",
  url="https://www.fit.vut.cz/research/publication/11012/"
}