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