Enabling Research Through The SCIP Optimization Suite 8.0

Ksenia Bestuzheva, Mathieu Besancon, Wei-Kun Chen, Antonia Chmiela, Tim Donkiewicz, Jasper van Doornmalen, Leon Eifler, Oliver Gaul, Gerald Gamrath, Ambros Gleixner, Leona Gottwald, Christoph Graczyk, Katrin Halbig, Alexander Hoen, Christopher Hojny, Rolf van der Hulst, Thorsten Koch, Marco Lübbecke, Stephen J. Maher, Frederic MatterErik Mühmer, Benjamin Müller, Marc E. Pfetsch, Daniel Rehfeldt, Steffan Schlein, Franziska Schlösser, Felipe Serrano, Yuji Shinano, Boro Sofranac, Mark Turner, Stefan Vigerske, Fabian Wegscheider, Philipp Wellner, Dieter Weninger, Jakob Witzig

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)
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Abstract

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. The focus of this article is on the role of the SCIP Optimization Suite in supporting research. SCIP's main design principles are discussed, followed by a presentation of the latest performance improvements and developments in version 8.0, which serve both as examples of SCIP's application as a research tool and as a platform for further developments. Furthermore, this article gives an overview of interfaces to other programming and modeling languages, new features that expand the possibilities for user interaction with the framework, and the latest developments in several extensions built upon SCIP.

Original languageEnglish
Article number22
Pages (from-to)1-21
Number of pages21
JournalACM Transactions on Mathematical Software
Volume49
Issue number2
DOIs
Publication statusPublished - 15 Jun 2023

Keywords

  • Constraint integer programming
  • branch-and-cut
  • branch-and-price
  • column generation
  • linear programming
  • mixed-integer linear programming
  • mixed-integer nonlinear programming
  • mixed-integer semidefinite programming
  • optimization solver
  • parallelization

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