Synchronous and Asynchronous Migration in Adaptive Differential Evolution Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F13%3AA13015U5" target="_blank" >RIV/61988987:17310/13:A13015U5 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
čeština
Original language name
Synchronous and Asynchronous Migration in Adaptive Differential Evolution Algorithms
Original language description
The influence of synchronous and asynchronous migration on the performance of adaptive differential evolution algorithms is investigated. Six adaptive differential evolution variants are employed by the parallel migration model with a~star topology. Synchronous and asynchronous migration models with various parameters settings were experimentally compared with non-parallel adaptive algorithms in six shifted benchmark problems of dimension D=30. Three different ways of exchanging individuals are appliedin a synchronous island model with a fixed number of islands. Three different numbers of sub-populations are set up in an asynchronous island model. The parallel synchronous and asynchronous migration models increase performance in most problems.
Czech name
Synchronous and Asynchronous Migration in Adaptive Differential Evolution Algorithms
Czech description
The influence of synchronous and asynchronous migration on the performance of adaptive differential evolution algorithms is investigated. Six adaptive differential evolution variants are employed by the parallel migration model with a~star topology. Synchronous and asynchronous migration models with various parameters settings were experimentally compared with non-parallel adaptive algorithms in six shifted benchmark problems of dimension D=30. Three different ways of exchanging individuals are appliedin a synchronous island model with a fixed number of islands. Three different numbers of sub-populations are set up in an asynchronous island model. The parallel synchronous and asynchronous migration models increase performance in most problems.
Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
NEURAL NETWORK WORLD
ISSN
1210-0552
e-ISSN
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Volume of the periodical
23
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
14
Pages from-to
17-30
UT code for WoS article
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EID of the result in the Scopus database
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