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

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/4149 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/4149 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/4149 archive 351 disk0/00/00/45/89 2016-01-15 02:06:32 2021-08-27 17:15:24 2016-01-15 02:06:32 monograph show 2 Pflug G.C. 1361 0000-0001-8215-3550 Ruszczynski A. 1475 Schultz R. On the Glivenko-Cantelli Problem in Stochastic Programming: Linear Recourse pub iis_cmp iis_met iis_sys prog_opt 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. 1995-01 published WP-95-003 WP-95-003 10 229 1544 public working_paper IIASA, Laxenburg, Austria 18 FALSE info:eu-repo/semantics/book