A surrogate-assisted evolution strategy for constrained multi-objective optimization

•New surrogate-assisted ES for constrained multi-objective optimization is developed.•Surrogates are used to identify the most promising among many trial offspring.•A radial basis function (RBF) model is used to implement the method.•Method is tested on benchmark problems and manufacturing and robot...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Expert systems with applications Jg. 57; S. 270 - 284
Hauptverfasser:	Datta, Rituparna, Regis, Rommel G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.09.2016
Schlagworte:	Algorithms Approximation Computation Computer simulation Constrained optimization Constraints Evolution strategy Mathematical analysis Mathematical models Metamodel Multi-objective optimization Optimization Radial basis function Surrogate Radial basis function Multi-objective optimization Evolution strategy Surrogate Metamodel Constrained optimization
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!