Solving mixed integer linear and nonlinear problems using the SCIP Optimization Suite
Please always quote using this URN: urn:nbn:de:0297-zib-15654
- This paper introduces the SCIP Optimization Suite and discusses the capabilities of its three components: the modeling language Zimpl, the linear programming solver SoPlex, and the constraint integer programming framework SCIP. We explain how these can be used in concert to model and solve challenging mixed integer linear and nonlinear optimization problems. SCIP is currently one of the fastest non-commercial MIP and MINLP solvers. We demonstrate the usage of Zimpl, SCIP, and SoPlex by selected examples, we give an overview of available interfaces, and outline plans for future development.
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| Author: | Timo BertholdORCiD, Gerald GamrathORCiD, Ambros GleixnerORCiD, Stefan Heinz, Thorsten KochORCiD, Yuji ShinanoORCiD |
|---|---|
| Document Type: | ZIB-Report |
| Tag: | LP, MIP, CIP, MINLP, modeling, optimization, SCIP, SoPlex, Zimpl |
| MSC-Classification: | 90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C05 Linear programming |
| 90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C11 Mixed integer programming | |
| 90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C26 Nonconvex programming, global optimization | |
| Date of first Publication: | 2012/07/31 |
| Series (Serial Number): | ZIB-Report (12-27) |
| ISSN: | 1438-0064 |
