A coevolutionary constrained multi-objective algorithm with a learning constraint boundary

When solving constrained multi-objective optimization problems, the balance of convergence, diversity, and feasibility plays a pivotal role. To address this issue, this paper proposes a coevolutionary constrained multi-objective algorithm with learning constraint boundary (CCMOLCB). Firstly, the con...

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Bibliographic Details

Published in:	Applied soft computing Vol. 148; p. 110845
Main Authors:	Cao, Jie, Yan, Zesen, Chen, Zuohan, Zhang, Jianlin
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.11.2023
Subjects:	Constrained multi-objective evolutionary algorithms Constrained multi-objective optimization Multiple-populations Constrained multi-objective optimization Multiple-populations Constrained multi-objective evolutionary algorithms
ISSN:	1568-4946, 1872-9681
Online Access:	Get full text
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