Name
Abstract | ||
|---|---|---|
We discuss the variability in the performance of multiple runs of branch-and-cut mixed integer linear programming solvers, and we concentrate on the one deriving from the use of different optimal bases of the linear programming relaxations. We propose a new algorithm exploiting more than one of those bases and we show that different versions of the algorithm can be used to stabilize and improve the performance of the solver. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s12532-015-0096-0 | Math. Program. Comput. |
Keywords | Field | DocType |
Integer programming, Performance variability, 90C10 Integer programming, 90C11 Mixed Integer programming, 90-08 Computational methods | Mathematical optimization,Computer science,Branch and price,Branch and cut,Algorithm,Integer programming,Software,Linear programming,Sampling (statistics),Solver | Journal |
Volume | Issue | ISSN |
8 | 1 | 1867-2957 |
Citations | PageRank | References |
5 | 0.47 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matteo Fischetti | 1 | 2505 | 260.53 |
| Andrea Lodi | 2 | 2198 | 152.51 |
| Michele Monaci | 3 | 1049 | 60.78 |
| Domenico Salvagnin | 4 | 289 | 21.05 |
| Andrea Tramontani | 5 | 96 | 6.05 |