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 Berthold, Gerald Gamrath, Ambros M. Gleixner, Stefan Heinz, Thorsten Koch, Yuji Shinano
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

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