Cooperative Model of Evolutionary Algorithms Applied to CEC 2019 Single Objective Numerical Optimization

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F19%3AA2001ZZZ" target="_blank" >RIV/61988987:17310/19:A2001ZZZ - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/CEC.2019.8790317" target="_blank" >http://dx.doi.org/10.1109/CEC.2019.8790317</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC.2019.8790317" target="_blank" >10.1109/CEC.2019.8790317</a>

Result language
angličtina
Original language name
Cooperative Model of Evolutionary Algorithms Applied to CEC 2019 Single Objective Numerical Optimization
Original language description
A cooperative model of well-known evolutionaryalgorithms is proposed and tested on CEC 2019 benchmark suite. The four adaptive algorithms are chosen for this model, namely Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) and three variants of adaptive Differential Evolution. Although the three algorithms use constant population size, the proposed model employs an efficient linear population size reduction mechanism. The provided results show that theCooperative Model of Evolutionary Algorithms (CMEAL) is able to solve seven out of ten optimization problems.
Czech name
—
Czech description
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Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2019 IEEE Congress on Evolutionary Computation (CEC)
ISBN
978-1-7281-2153-6
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
358-363
Publisher name
IEEE
Place of publication
Piscataway, NJ, USA
Event location
New Zealand
Event date
Jun 10, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000502087100049

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