Evolutionary optimization with active learning of surrogate models and fixed evaluation batch size
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F12%3A00200867" target="_blank" >RIV/68407700:21340/12:00200867 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/12:00384885
Result on the web
<a href="http://itat.ics.upjs.sk/Site/Zborniky" target="_blank" >http://itat.ics.upjs.sk/Site/Zborniky</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Evolutionary optimization with active learning of surrogate models and fixed evaluation batch size
Original language description
Evolutionary optimization is often applied to problems, where simulations or experiments used as the fit ness function are expensive to run. In such cases, surro gate models are used to reduce the number of fitness eval uations. Some of the problems alsorequire a fixed size batch of solutions to be evaluated at a time. Traditional methods of selecting individuals for true evaluation to im prove the surrogate model either require individual points to be evaluated, or couple the batch size with the EA gener ation size. We propose a queue based method for individual selection based on active learning of a kriging model. Indi viduals are selected using the confidence intervals predicted by the model, added to a queue and evaluated once the queue length reaches the batch size. The method was tested on several standard benchmark problems. Results show that the proposed algorithm is able to achieve a solution using significantly less evaluations of the true fitness function. The effect of th
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA201%2F08%2F0802" target="_blank" >GA201/08/0802: Applications of Methods of Knowledge Engineering in Data Mining</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
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 Conference on Theory and Practice of information Technologies
ISBN
978-80-971144-0-4
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
33-40
Publisher name
Univerzita P. J. Šafárika
Place of publication
Košice
Event location
Belianské Tatry
Event date
Sep 17, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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