Constrained multi-objective evolutionary algorithm with an improved two-archive strategy

Solving constrained multi-objective optimization problems (CMOPs) obtains considerable attention in the evolutionary computation community. Various constrained multi-objective evolutionary algorithms (CMOEAs) have been developed for the CMOPs in the last few decades. Among the CMOEA techniques, two...

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Bibliographic Details
Published in:	Knowledge-based systems Vol. 246; p. 108732
Main Authors:	Li, Wei, Gong, Wenyin, Ming, Fei, Wang, Ling
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 21.06.2022 Elsevier Science Ltd
Subjects:	Algorithms Archives & records Computation Constrained multi-objective optimization Convergence Evaluation Evolutionary algorithm Evolutionary algorithms Evolutionary computation Experiments Fitness Fitness evaluation Genetic algorithms Mating Mating selection Multiple objective analysis Objectives Optimization Strategies Strategy Two archive Constrained multi-objective optimization Fitness evaluation Mating selection Evolutionary algorithm Two archive
ISSN:	0950-7051, 1872-7409
Online Access:	Get full text
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