Active Robust Optimization: Enhancing Robustness to Uncertain Environments

Many real world optimization problems involve uncertainties. A solution for such a problem is expected to be robust to these uncertainties. Commonly, robustness is attained by choosing the solution's parameters such that the solution's performance is less influenced by negative effects of...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on cybernetics Jg. 44; H. 11; S. 2221 - 2231
Hauptverfasser:	Salomon, Shaul, Avigad, Gideon, Fleming, Peter J., Purshouse, Robin C.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.11.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptation Adaptive design Algorithms Artificial Intelligence Brightness Computer Simulation Cybernetics Decision Support Techniques dynamic optimization Dynamic tests Ecosystem Equivalence evolutionary algorithms Expenses Feedback Linear programming Models, Statistical multiobjective optimization Nonlinear programming Optimization Pareto optimization Pattern Recognition, Automated - methods robust optimization Robustness Tables (data) Uncertainty Vectors multiobjective optimization Adaptive design dynamic optimization evolutionary algorithms robust optimization
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!