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

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.

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Year of publication:	1995-01
Authors:	Pflug, G.C. ; Ruszczynski, A. ; Schultz, R.
Institutions:	International Institute for Applied Systems Analysis (IIASA)

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

Persistent link: https://www.econbiz.de/10005837852