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

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Pflug, G.C. ORCID: https://orcid.org/0000-0001-8215-3550, Ruszczynski, A., & Schultz, R. (1995). On the Glivenko-Cantelli Problem in Stochastic Programming: Linear Recourse. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-95-003

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Abstract

Integrals of optimal values of random linear programming problems depending on a finite dimensional parameter are approximated by using empirical distributions instead of the original measure. Uniform convergence of the approximations is proved under fairly broad conditions allowing non-convex or discontinuous dependence on the parameter value and random size of the linear programming problem.

Item Type: Monograph (IIASA Working Paper)
Research Programs: Optimization under Uncertainty (OPT)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:06
Last Modified: 27 Aug 2021 17:15
URI: https://pure.iiasa.ac.at/4589

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