Name
Abstract | ||
|---|---|---|
In this paper a class of robust two-stage combinatorial optimization problems is discussed. It is assumed that the uncertain second stage costs are specified in the form of a convex uncertainty set, in particular polyhedral or ellipsoidal ones. It is shown that the robust two-stage versions of basic network and selection problems are NP-hard, even in a very restrictive cases. Some exact and approximation algorithms for the general problem are constructed. Polynomial and approximation algorithms for the robust two-stage versions of basic problems, such as the selection and shortest path problems, are also provided. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Data Structures and Algorithms | Journal |
Volume | Citations | PageRank |
abs/1905.02469 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marc Goerigk | 1 | 72 | 14.77 |
| Adam Kasperski | 2 | 352 | 33.64 |
| Paweł Zieliński | 3 | 227 | 28.62 |