A multi-objective evolutionary algorithm for steady-state constrained multi-objective optimization problems

Many multi-objective evolutionary algorithms (MOEAs) are developed to solve constrained multi-objective optimization problems (CMOPs). However, they encounter low efficiency for steady-state CMOPs which are to optimize a known feasible solution named the current steady-state operation point. This pa...

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Bibliographic Details

Published in:	Applied soft computing Vol. 101; p. 107042
Main Authors:	Yang, Yongkuan, Liu, Jianchang, Tan, Shubin
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.03.2021
Subjects:	Co-evolution Multi-objective evolutionary algorithm Steady-state constrained multi-objective optimization Multi-objective evolutionary algorithm Steady-state constrained multi-objective optimization Co-evolution
ISSN:	1568-4946, 1872-9681
Online Access:	Get full text
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