The Competing Genes Evolutionary Algorithm: Avoiding Genetic Drift Through Competition, Local Search, and Majority Voting

An estimation-of-distribution algorithm is an evolutionary algorithm that uses a probabilistic model to represent its population. It iteratively draws solutions from its model and, considering their fitnesses, uses these solutions to update the model's parameters. However, there is a risk of re...

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Bibliographic Details
Published in:	IEEE transactions on evolutionary computation Vol. 27; no. 6; pp. 1678 - 1689
Main Authors:	Ajimakin, Adetunji David, Devi, V. Susheela
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.12.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Computational modeling Estimation-of-distribution algorithms (EDAs) Evolutionary algorithms Evolutionary computation Gauss–Southwell rule Genes Genetic algorithms genetic drift Genetics Iterative methods local search majority voting Markov processes natural gradient Parameters Probabilistic models Random noise Runtime runtime analysis Search process Sociology Statistics Upper bounds
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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