Eigen Crossover in Cooperative Model of Evolutionary Algorithms Applied to CEC 2022 Single Objective Numerical Optimisation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F22%3AA2302GV8" target="_blank" >RIV/61988987:17310/22:A2302GV8 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9870433" target="_blank" >https://ieeexplore.ieee.org/document/9870433</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC55065.2022.9870433" target="_blank" >10.1109/CEC55065.2022.9870433</a>
Alternative languages
Result language
angličtina
Original language name
Eigen Crossover in Cooperative Model of Evolutionary Algorithms Applied to CEC 2022 Single Objective Numerical Optimisation
Original language description
In this paper, a cooperative model of four well-performing evolutionary algorithms enhanced by Eigen crossover is proposed and applied to a set of problems CEC 2022. The four adaptive algorithms employed in this model are - Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES), Differential Evolution with Covariance Matrix Learning and Bimodal Distribution Parameter Setting (CoBiDE), an adaptive variant of jSO, and Differential Evolution With an Individual-Dependent Mechanism (IDE). For the higher efficiency of the cooperative model, a linear population-size reduction mechanism is employed. The model was introduced for CEC 2019. Here, Eigen crossover is applied for each cooperating algorithm. The provided results show that the proposed model of four Evolutionary Algorithms with Eigen crossover (EA4eig) is able to solve ten out of 24 optimisation problems. Moreover, comparing EA4eig with four state-of-the-art variants of adaptive Differential Evolution illustrates the superiority of the newly designed optimiser.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2022 IEEE Congress on Evolutionary Computation (CEC)
ISBN
978-1-6654-6708-7
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1-8
Publisher name
IEEE
Place of publication
Piscataway, NJ, USA
Event location
Padua, Italy
Event date
Jul 18, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000859282000214