Handling multi-objective optimization problems with unbalanced constraints and their effects on evolutionary algorithm performance

Despite the successful application of an extension of the Multi-Objective Evolution Algorithm based on Decomposition (MOEA/D-M2M) to solve unbalanced multi-objective optimization problems (UMOPs), its use in constrained unbalanced multi-objective optimization problems has not been fully explored. In...

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Veröffentlicht in:	Swarm and evolutionary computation Jg. 55; S. 100676
Hauptverfasser:	Peng, Chaoda, Liu, Hai-Lin, Goodman, Erik D.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.06.2020
Schlagworte:	Constraint-handling technique Evolutionary algorithm MOEA/D-M2M Multi-objective Unbalanced constraints Multi-objective Constraint-handling technique Unbalanced constraints MOEA/D-M2M Evolutionary algorithm
ISSN:	2210-6502
Online-Zugang:	Volltext
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