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

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.

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Year of publication:	1996-02
Authors:	Pflug, G.C. ; Ruszczynski, A. ; Schultz, R.
Institutions:	International Institute for Applied Systems Analysis (IIASA)

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Extent:	application/pdf application/postscript
Series:	Working Papers.
Type of publication:	Book / Working Paper
Language:	English
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005837873