A surrogate-assisted a priori multiobjective evolutionary algorithm for constrained multiobjective optimization problems

We consider multiobjective optimization problems with at least one computationally expensive constraint function and propose a novel surrogate-assisted evolutionary algorithm that can incorporate preference information given a priori. We employ Kriging models to approximate expensive objective and c...

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Veröffentlicht in:	Journal of global optimization Jg. 90; H. 2; S. 459 - 485
Hauptverfasser:	Aghaei pour, Pouya, Hakanen, Jussi, Miettinen, Kaisa
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.10.2024 Springer Springer Nature B.V
Schlagworte:	Algorithms Analysis Computer Science Constraints Evolutionary algorithms Genetic algorithms Mathematics Mathematics and Statistics Multiple objective analysis Operations Research/Decision Theory Optimization Performance evaluation Real Functions Constraint handling Multiple objectives Surrogate-assisted optimization A priori algorithms Constrained problems Model management Computationally expensive problems
ISSN:	0925-5001, 1573-2916
Online-Zugang:	Volltext
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