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| Content Provider | Springer Nature Link |
|---|---|
| Author | Schultz, Rüdiger |
| Copyright Year | 2003 |
| Abstract |  Including integer variables into traditional stochastic linear programs has considerable implications for structural analysis and algorithm design. Starting from mean-risk approaches with different risk measures we identify corresponding two- and multi-stage stochastic integer programs that are large-scale block-structured mixed-integer linear programs if the underlying probability distributions are discrete. We highlight the role of mixed-integer value functions for structure and stability of stochastic integer programs. When applied to the block structures in stochastic integer programming, well known algorithmic principles such as branch-and-bound, Lagrangian relaxation, or cutting plane methods open up new directions of research. We review existing results in the field and indicate departure points for their extension. |
| Starting Page | 285 |
| Ending Page | 309 |
| Page Count | 25 |
| File Format | |
| ISSN | 00255610 |
| Journal | Mathematical Programming |
| Volume Number | 97 |
| Issue Number | 1-2 |
| e-ISSN | 14364646 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2003-07-01 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Mathematics Software |
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