Article ID: | iaor200948530 |
Country: | United States |
Volume: | 32 |
Issue: | 1 |
Start Page Number: | 118 |
End Page Number: | 135 |
Publication Date: | Feb 2007 |
Journal: | Mathematics of Operations Research |
Authors: | Rmisch Werner, Eichhorn Andreas |
Keywords: | programming: probabilistic |
We consider empirical approximations (sample average 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 resampling methods (bootstrap, subsampling).