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The SCIP Optimization Suite 6.0

Gleixner, Ambros M. ; Bastubbe, Michael ; Eifler, Leon ; Gally, Tristan ; Gamrath, Gerald ; Gottwald, Robert L. ; Hendel, Gregor ; Hojny, Christoper ; Koch, Thorsten ; Lübbecke, Marco E. ; Maher, Stephen J. ; Miltenberger, Matthias ; Müller, Benjamin ; Pfetsch, Marc E. ; Puchert, Christian ; Rehfeldt, Daniel ; Schlösser, Franziska ; Schubert, Christoph ; Serrano, Felipe ; Shinano, Yuji ; Viernickel, Jan Merlin ; Walter, Matthias ; Wegscheider, Fabian ; Witt, Jonas T. ; Witzig, Jakob (2018)
The SCIP Optimization Suite 6.0.
In: ZIB-Report, 18-26
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 6.0 of the SCIP Optimization Suite. Besides performance improvements of the MIP and MINLP core achieved by new primal heuristics and a new selection criterion for cutting planes, one focus of this release are decomposition algorithms. Both SCIP and the automatic decomposition solver GCG now include advanced functionality for performing Benders’ decomposition in a generic framework. GCG’s detection loop for structured matrices and the coordination of pricing routines for Dantzig-Wolfe decomposition has been significantly revised for greater flexibility. Two SCIP extensions have been added to solve the recursive circle packing problem by a problem-specific column generation scheme and to demonstrate the use of the new Benders’ framework for stochastic capacitated facility location. Last, not least, the report presents updates and additions to the other components and extensions of the SCIP Optimization Suite: the LP solver SoPlex, the modeling language Zimpl, the parallelization framework UG, the Steiner tree solver SCIP-Jack, and the mixed-integer semidefinite programming solver SCIP-SDP.

Typ des Eintrags: Artikel
Erschienen: 2018
Autor(en): Gleixner, Ambros M. ; Bastubbe, Michael ; Eifler, Leon ; Gally, Tristan ; Gamrath, Gerald ; Gottwald, Robert L. ; Hendel, Gregor ; Hojny, Christoper ; Koch, Thorsten ; Lübbecke, Marco E. ; Maher, Stephen J. ; Miltenberger, Matthias ; Müller, Benjamin ; Pfetsch, Marc E. ; Puchert, Christian ; Rehfeldt, Daniel ; Schlösser, Franziska ; Schubert, Christoph ; Serrano, Felipe ; Shinano, Yuji ; Viernickel, Jan Merlin ; Walter, Matthias ; Wegscheider, Fabian ; Witt, Jonas T. ; Witzig, Jakob
Art des Eintrags: Bibliographie
Titel: The SCIP Optimization Suite 6.0
Sprache: Englisch
Publikationsjahr: 2 Juli 2018
Ort: Berlin
Verlag: Zuse Institute Berlin
Titel der Zeitschrift, Zeitung oder Schriftenreihe: ZIB-Report
Jahrgang/Volume einer Zeitschrift: 18-26
URL / URN: urn:nbn:de:0297-zib-69361
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Kurzbeschreibung (Abstract):

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 6.0 of the SCIP Optimization Suite. Besides performance improvements of the MIP and MINLP core achieved by new primal heuristics and a new selection criterion for cutting planes, one focus of this release are decomposition algorithms. Both SCIP and the automatic decomposition solver GCG now include advanced functionality for performing Benders’ decomposition in a generic framework. GCG’s detection loop for structured matrices and the coordination of pricing routines for Dantzig-Wolfe decomposition has been significantly revised for greater flexibility. Two SCIP extensions have been added to solve the recursive circle packing problem by a problem-specific column generation scheme and to demonstrate the use of the new Benders’ framework for stochastic capacitated facility location. Last, not least, the report presents updates and additions to the other components and extensions of the SCIP Optimization Suite: the LP solver SoPlex, the modeling language Zimpl, the parallelization framework UG, the Steiner tree solver SCIP-Jack, and the mixed-integer semidefinite programming solver SCIP-SDP.

Fachbereich(e)/-gebiet(e): DFG-Sonderforschungsbereiche (inkl. Transregio)
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche
04 Fachbereich Mathematik
04 Fachbereich Mathematik > Optimierung
04 Fachbereich Mathematik > Optimierung > Discrete Optimization
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 805: Beherrschung von Unsicherheit in lasttragenden Systemen des Maschinenbaus
Hinterlegungsdatum: 18 Jul 2018 10:17
Letzte Änderung: 11 Aug 2023 09:10
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