On the Glivenko-Cantelli Problem in Stochastic Programming: Linear Recourse and Extensions

Pflug GC, Ruszczynski A, & Schultz R (1996). On the Glivenko-Cantelli Problem in Stochastic Programming: Linear Recourse and Extensions. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-96-020

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Abstract

Integrals of optimal values of random optimization problems depending on a finite dimensional parameter are approximated by using empirical distributions instead of the original measure. Under fairly broad conditions, it is proved that uniform convergence of empirical approximations of the right hand sides of the constraints implies uniform convergence of the optimal values in the linear and convex case.

Item Type: Monograph (IIASA Working Paper)
Research Programs: Optimization under Uncertainty (OPT)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:08
Last Modified: 23 Jul 2016 11:07
URI: http://pure.iiasa.ac.at/5005

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