A Supervised Surrogate-Assisted Evolutionary Algorithm for Complex Optimization Problems

Surrogate-assisted evolutionary algorithms (SAEAs), which use surrogate models to evaluate the individuals' fitness, show high efficiency in solving complex optimization problems. In an SAEA, the solution quality and algorithm efficiency are the two most concerned performance measures. It is ne...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on instrumentation and measurement Jg. 72; S. 1
Hauptverfasser:	Zhao, Xin, Jia, Xue, Zhang, Tao, Liu, Tianwei, Cao, Yahui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	algorithm efficiency Computational modeling Computing time Efficiency Evolutionary algorithms Finite element method Fitness Genetic algorithms Mathematical models new individual generation strategy Optimization Sociology solution quality Statistics Supervised surrogate-assisted evolutionary algorithm surrogate model management strategy Training
ISSN:	0018-9456, 1557-9662
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!