eprintid: 14189
rev_number: 7
eprint_status: archive
userid: 5
dir: disk0/00/01/41/89
datestamp: 2016-12-21 10:27:09
lastmod: 2021-08-27 17:28:18
status_changed: 2016-12-21 10:27:09
type: article
metadata_visibility: show
item_issues_count: 2
creators_name: Pflug, G.
creators_name: Ruszczynski, A.
creators_name: Schultz, R.
creators_id: 1361
creators_id: 1475
creators_orcid: 0000-0001-8215-3550
title: On the Glivenko-Cantelli Problem in Stochastic Programming: Linear Recourse and Extensions
ispublished: pub
divisions: prog_opt
abstract: 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.
date: 1998
date_type: published
publisher: INFORMS
id_number: 10.1287/moor.23.1.204
creators_browse_id: 229
creators_browse_id: 1544
full_text_status: none
publication: Mathematics of Operations Research
volume: 23
number: 1
pagerange: 204-220
refereed: TRUE
issn: 0364-765X
coversheets_dirty: FALSE
fp7_type: info:eu-repo/semantics/article
citation:   Pflug, G. <https://pure.iiasa.ac.at/view/iiasa/229.html> ORCID: https://orcid.org/0000-0001-8215-3550 <https://orcid.org/0000-0001-8215-3550>, Ruszczynski, A. <https://pure.iiasa.ac.at/view/iiasa/1544.html>, & Schultz, R.  (1998).  On the Glivenko-Cantelli Problem in Stochastic Programming: Linear Recourse and Extensions.   Mathematics of Operations Research 23 (1) 204-220. 10.1287/moor.23.1.204 <https://doi.org/10.1287/moor.23.1.204>.