Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm with Model Migration.
Result description
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 island-based version of copula-based EDA with probabilistic model migration (mCEDA) was tested on a set of well-known 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 copula-based EDAs.
Keywords
Estimation of Distribution AlgorithmsCopula TheoryParallel EDAIsland-based ModelMultivariate Copula SamplingMigration of Probabilistic Models
The result's identifiers
Result code in IS VaVaI
Result on the web
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Elliptical and Archimedean Copulas in Estimation of Distribution Algorithm with Model Migration.
Original language description
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 island-based version of copula-based EDA with probabilistic model migration (mCEDA) was tested on a set of well-known 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 copula-based EDAs.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015)
ISBN
978-989-758-157-1
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
212-219
Publisher name
SciTePress - Science and Technology Publications
Place of publication
Lisbon
Event location
Lisbon
Event date
Nov 12, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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Basic information
Result type
D - Article in proceedings
OECD FORD
Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Year of implementation
2015