Combining multiobjective and single-objective genetic algorithms in heterogeneous island model

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F10%3A10056962" target="_blank" >RIV/00216208:11320/10:10056962 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/10:00358846
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Combining multiobjective and single-objective genetic algorithms in heterogeneous island model
Original language description
The majority of multiobjective genetic algorithms is computationally expensive, therefore they often need to be parallelized before they can be used to solve practical tasks. Parallelization of multiobjective genetic algorithms is a relatively studied area, but no clearly winning approach has appeared yet. In this paper we present a novel parallel hybrid algorithm which combines multiobjective and single-objective genetic algorithms. We how that this algorithm can be successfully used to solve multiobjective optimization problems while outperforming more traditional parallel versions of multiobjective genetic algorithms.
Czech name
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Czech description
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Project
<a href="/en/project/OC10047" target="_blank" >OC10047: Analysis of Intelligent Computational Distributed Systems</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2010)
ISBN
978-1-4244-6910-9
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
IEEE
Place of publication
Neuveden
Event location
Barcelona, Španělsko
Event date
Jul 18, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000287375801047

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