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The SCIP Optimization Suite 8.0

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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 8.0 of the SCIP Optimization Suite. Major updates in SCIP include improvements in symmetry handling and decomposition algorithms, new cutting planes, a new plugin type for cut selection, and a complete rework of the way nonlinear constraints are handled. Additionally, SCIP 8.0 now supports interfaces for Julia as well as Matlab. Further, UG now includes a unified framework to parallelize all solvers, a utility to analyze computational experiments has been added to GCG, dual solutions can be postsolved by PaPILO, new heuristics and presolving methods were added to SCIP-SDP, and additional problem classes and major performance improvements are available in SCIP-Jack.

Ksenia Bestuzheva, Mathieu Besan\c{c}on, 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 L\"ubbecke, Stephen J. Maher, Frederic Matter, Erik M\"uhmer, Benjamin M\"uller, Marc E. Pfetsch, Daniel Rehfeldt, Steffan Schlein, Franziska Schl\"osser, Felipe Serrano, Yuji Shinano, Boro Sofranac, Mark Turner, Stefan Vigerske, Fabian Wegscheider, Philipp Wellner, Dieter Weninger, Jakob Witzig• 2021

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TaskDatasetResultRank
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Execution Time100
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Mixed Integer Linear Programming SolvingCapacitated Facility Location 200x100 (Medium)
Nodes Explored138
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Combinatorial AuctionCombinatorial Auction (CA) medium-scale
Objective Value7.14e+3
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Combinatorial OptimizationSet Covering Small s
Time (s)6.7
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Capacitated Facility LocationCapacitated Facility Location (CFL) medium-scale
Objective Value9.07e+3
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Mixed Integer Linear ProgrammingLarge-scale Capacitated Facility Location (CFL) (test)
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Set CoverSet Cover (SC) medium-scale
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Maximum Independent SetMIS Large-scale
Objective Value304.7
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MILP separator configurationTang Bin. Pack. (test)
Median Relative Time Improvement0.00e+0
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Mixed Integer Linear ProgrammingLarge-scale Maximum Independent Set (MIS) (test)
Objective Value304.7
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