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

G.C. Pflug, Andrzej Ruszczynski () and R. Schultz

Working Papers from International Institute for Applied Systems Analysis

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.

Date: 1995-01
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