SCIP

SCIP is currently one of the fastest non-commercial solvers for mixed integer programming (MIP) and mixed integer nonlinear programming (MINLP). It is also a framework for constraint integer programming and branch-cut-and-price. It allows for total control of the solution process and the access of detailed information down to the guts of the solver. SCIP is part of the SCIP Optimization Suite, which also contains the LP solver SoPlex, the modelling language ZIMPL, the parallelization framework UG and the generic column generation solver GCG.

This software is also peer reviewed by journal MPC.


References in zbMATH (referenced in 193 articles , 4 standard articles )

Showing results 1 to 20 of 193.
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  1. Ichim, Bogdan; Katthän, Lukas; Moyano-Fernández, Julio José: How to compute the Stanley depth of a module (2017)
  2. Berthold, Timo; Farmer, James; Heinz, Stefan; Perregaard, Michael: Parallelization of the FICO Xpress-Optimizer (2016)
  3. Borndörfer, Ralf; Schenker, Sebastian; Skutella, Martin; Strunk, Timo: PolySCIP (2016)
  4. Braun, Gábor; Pokutta, Sebastian: A polyhedral characterization of border bases (2016)
  5. Bruns, Winfried; Sieg, Richard; Söger, Christof: The subdivision of large simplicial cones in normaliz (2016)
  6. Buchheim, Christoph; De Santis, Marianna; Lucidi, Stefano; Rinaldi, Francesco; Trieu, Long: A feasible active set method with reoptimization for convex quadratic mixed-integer programming (2016)
  7. Friberg, Henrik A.: CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization (2016)
  8. Greuel, Gert-Martin (ed.); Koch, Thorsten (ed.); Paule, Peter (ed.); Sommese, Andrew (ed.): Mathematical software -- ICMS 2016. 5th international conference, Berlin, Germany, July 11--14, 2016. Proceedings (2016)
  9. Grimm, Veronika; Martin, Alexander; Schmidt, Martin; Weibelzahl, Martin; Zöttl, Gregor: Transmission and generation investment in electricity markets: the effects of market splitting and network fee regimes (2016)
  10. Hojny, Christopher; Pfetsch, Marc E.: A polyhedral investigation of star colorings (2016)
  11. Johnston, Matthew D.: A linear programming approach to dynamical equivalence, linear conjugacy, and the deficiency one theorem (2016)
  12. Johnston, Matthew D.; Pantea, Casian; Donnell, Pete: A computational approach to persistence, permanence, and endotacticity of biochemical reaction systems (2016)
  13. Kimura, Keiji; Waki, Hayato: Mixed integer nonlinear program for minimization of Akaike’s information criterion (2016)
  14. Ku, Wen-Yang; Beck, J.Christopher: Mixed integer programming models for job shop scheduling: A computational analysis (2016)
  15. Maher, Stephen; Miltenberger, Matthias; Pedroso, João Pedro; Rehfeldt, Daniel; Schwarz, Robert; Serrano, Felipe: PySCIPOpt: mathematical programming in python with the SCIP optimization suite (2016)
  16. Modaresi, Sina; Kılınç, Mustafa R.; Vielma, Juan Pablo: Intersection cuts for nonlinear integer programming: convexification techniques for structured sets (2016)
  17. Newby, Eric; Ali, M.Montaz: Transformation-based preprocessing for mixed-integer quadratic programs (2016)
  18. Oates, Chris.J.; Smith, Jim Q.; Mukherjee, Sach: Estimating causal structure using conditional DAG models (2016)
  19. Oates, Chris J.; Smith, Jim Q.; Mukherjee, Sach; Cussens, James: Exact estimation of multiple directed acyclic graphs (2016)
  20. Rose, Daniel; Schmidt, Martin; Steinbach, Marc C.; Willert, Bernhard M.: Computational optimization of gas compressor stations: MINLP models versus continuous reformulations (2016)

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Further publications can be found at: http://scip.zib.de/#work