Name
Abstract | ||
|---|---|---|
We propose an algorithm for solving the surrogate dual of a mixed integer program. The algorithm uses a trust region method based on a piecewise affine model of the dual surrogate value function. A new and much more flexible way of updating bounds on the surrogate dual's value is proposed, in which numerical experiments prove to be advantageous. A proof of convergence is given and numerical tests show that the method performance is better than a state of the art subgradient solver. Incorporation of the surrogate dual value as a cut added to the integer program is shown to greatly reduce solution times of a standard commercial solver on a specific class of problems. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s10957-014-0681-9 | J. Optimization Theory and Applications |
Keywords | DocType | Volume |
Surrogate dual, Integer programming, Trust regions methods, Nonsmooth optimization, Primary 90C11, 90C25, Secondary 90C08 | Journal | 167 |
Issue | ISSN | Citations |
2 | 1573-2878 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Natashia Boland | 1 | 726 | 67.11 |
| Andrew C. Eberhard | 2 | 11 | 1.89 |
| Angelos Tsoukalas | 3 | 77 | 6.51 |