Learning-Based Robust Optimization: Procedures and Statistical Guarantees

Robust optimization (RO) is a common approach to tractably obtain safeguarding solutions for optimization problems with uncertain constraints. In this paper, we study a statistical framework to integrate data into RO based on learning a prediction set using (combinations of) geometric shapes that ar...

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Veröffentlicht in:	Management science 2021-06, Vol.67 (6), p.3447-3467
Hauptverfasser:	Hong, L. Jeff, Huang, Zhiyuan, Lam, Henry
Format:	Artikel
Sprache:	eng
Schlagworte:	chance constraint Feasibility Learning Optimization prediction set learning Probability quantile estimation robust optimization Statistical analysis Stochastic models Validity
Online-Zugang:	Volltext
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