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Stochastic integer programming: Limit theorems and confidence intervals

Please always quote using this URN:urn:nbn:de:0296-matheon-2062
  • We consider empirical approximations of two-stage stochastic mixed-integer linear programs and derive central limit theorems for the objectives and optimal values. The limit theorems are based on empirical process theory and the functional delta method. We also show how these limit theorems can be used to derive confidence intervals for optimal values via a certain modification of the bootstrapping method.

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Metadaten
Author:Andreas Eichhorn, Werner Römisch
URN:urn:nbn:de:0296-matheon-2062
Referee:Fredi Tröltzsch
Document Type:Preprint, Research Center Matheon
Language:English
Date of first Publication:2005/11/01
Release Date:2005/06/01
Institute:Humboldt-Universität zu Berlin
Weierstraß-Institut für Angewandte Analysis und Stochastik (WIAS)
Preprint Number:193
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