| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1141523 | Discrete Optimization | 2015 | 14 Pages |
Abstract
We describe a general method for deriving new inequalities for integer programming formulations of combinatorial optimization problems. The inequalities, motivated by local search algorithms, are valid for all optimal solutions but not necessarily for all feasible solutions. These local search inequalities can help in either pruning the search tree at some nodes or in improving the bound of the LP relaxations.
Related Topics
Physical Sciences and Engineering
Mathematics
Control and Optimization
Authors
Giuseppe Lancia, Franca Rinaldi, Paolo Serafini,