Estimation Distribution Algorithm for mixed continuous-discrete optimization problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F02%3APU36221" target="_blank" >RIV/00216305:26230/02:PU36221 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Estimation Distribution Algorithm for mixed continuous-discrete optimization problems
Original language description
In recent few years expressive progress in the theory and practice of Estimation of Distribution Algorithms (EDA) [1] has appeared, where the classical genetic recombination operators are replaced by probability estimation and stochastic sampling techniques. In this paper we identify some disadvantages of present probabilistic models used in EDAs and propose more general and efficient model for continuous optimization problems based on the decision trees. The new variant of EDA is capable to solve mixedd continuous-discrete optimization problems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2002
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 2nd Euro-International Symposium on Computational Intelligence
ISBN
1-58603-256-9
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
227-232
Publisher name
IOS Press
Place of publication
Kosice
Event location
Kosice
Event date
Jun 16, 2002
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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