Abstract | ||
---|---|---|
Many industrial problems can be naturally formulated using mixed integer non-linear programming (MINLP) models and can be solved by spatial Branch&Bound (sBB) techniques. We study the impact of two important parts of sBB methods: bounds tightening (BT) and branching strategies. We extend a branching technique originally developed for MILP, reliability branching, to the MINLP case. Motivated by the demand for open-source solvers for real-world MINLP problems, we have developed an sBB software package named couenne (Convex Over-and Under-ENvelopes for Non-linear Estimation) and used it for extensive tests on several combinations of BT and branching techniques on a set of publicly available and real-world MINLP instances. We also compare the performance of couenne with a state-of-the-art MINLP solver. |
Year | DOI | Venue |
---|---|---|
2009 | 10.1080/10556780903087124 | Optimization Methods and Software |
Keywords | DocType | Volume |
non-convex minlp,non-linear estimation,convex over-and under-envelopes,extensive test,sbb software package,sbb method,real-world minlp instance,state-of-the-art minlp solver,minlp case,real-world minlp problem,important part,branch and bound | Journal | 24 |
Issue | ISSN | Citations |
4-5 | 1055-6788 | 200 |
PageRank | References | Authors |
6.57 | 32 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Pietro Belotti | 1 | 393 | 21.19 |
Jon Lee | 2 | 856 | 58.60 |
Leo Liberti | 3 | 1280 | 105.20 |
Francois Margot | 4 | 232 | 9.62 |
Andreas Wachter | 5 | 200 | 6.57 |