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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/" }
Documents
mendel15-0612-1855-CR.pdf