Localized probability of improvement for kriging based multi-objective optimization

Localized probability of improvement for kriging based multi-objective optimization

The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationall...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Open Physics 2017-12, Vol.15 (1), p.954-958
Hauptverfasser: Li, Yinjiang, Xiao, Song, Barba, Paolo Di, Rotaru, Mihai, Sykulski, Jan K.
Format: Artikel
Sprache:eng
Schlagworte:
85.70.-w
85.85.+j
87.10.Mn
89.20.Kk
kriging
multi-objective optimization
Pareto front
surrogate-based optimization
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationally fast and linearly scalable to higher dimensions.
ISSN:2391-5471
2391-5471
DOI:10.1515/phys-2017-0117