Competitive evaluation of selected evolutionary algorithms and SOMA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F13%3A43869756" target="_blank" >RIV/70883521:28140/13:43869756 - 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
Competitive evaluation of selected evolutionary algorithms and SOMA
Original language description
In this paper three evolutionary algorithms are compared, in particular, of the Self-Organizing Migration Algorithm (SOMA) as a most important one is put into the contrast with Differential Evolution (DE) and Particle Swarm Optimization (PSO). In order to compare performances of the above-mentioned algorithms, selected objective functions have been tested. In total 15 different benchmark functions were used and each considered algorithm was employed 100 times on each one producing 4500 set experimentalruns. Acquired results were then statistically evaluated and compared. The paper also describes individual parameters, strategies, and some of the termination criteria of the algorithms.
Czech name
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Czech description
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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
<a href="/en/project/ED2.1.00%2F03.0089" target="_blank" >ED2.1.00/03.0089: The Centre of Security, Information and Advanced Technologies (CEBIA-Tech)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
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
International Journal of Mathematics and Computers in Simulations
ISSN
1998-0159
e-ISSN
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Volume of the periodical
7
Issue of the periodical within the volume
1
Country of publishing house
GB - UNITED KINGDOM
Number of pages
8
Pages from-to
42-49
UT code for WoS article
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EID of the result in the Scopus database
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