Model-based evolutionary algorithms: a short survey

The evolutionary algorithms (EAs) are a family of nature-inspired algorithms widely used for solving complex optimization problems. Since the operators (e.g. crossover, mutation, selection) in most traditional EAs are developed on the basis of fixed heuristic rules or strategies, they are unable to...

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Bibliographic Details

Published in:	Complex & intelligent systems Vol. 4; no. 4; pp. 283 - 292
Main Authors:	Cheng, Ran, He, Cheng, Jin, Yaochu, Yao, Xin
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.12.2018 Springer Nature B.V
Subjects:	Complexity Computational Intelligence Crossovers Data Structures and Information Theory Engineering Evolutionary algorithms Genetic algorithms Machine learning Multiple objective analysis Optimization Survey and State of the Art Model-based evolutionary algorithms Estimation of distribution algorithms Surrogate modelling Inverse modelling
ISSN:	2199-4536, 2198-6053
Online Access:	Get full text
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