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.
Author: | Andreas Eichhorn, Werner Römisch |
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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 |