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 219 articles , 4 standard articles )

Showing results 1 to 20 of 219.
Sorted by year (citations)

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  1. Andrea Callia D’Iddio, Michael Huth: Manyopt: An Extensible Tool for Mixed, Non-Linear Optimization Through SMT Solving (2017) arXiv
  2. Brinkmann, Philip; Ziegler, Günter M.: A flag vector of a 3-sphere that is not the flag vector of a 4-polytope (2017)
  3. Gleixner, Ambros M.; Berthold, Timo; Müller, Benjamin; Weltge, Stefan: Three enhancements for optimization-based bound tightening (2017)
  4. Göttlich, Simone; Potschka, Andreas; Ziegler, Ute: Partial outer convexification for traffic light optimization in road networks (2017)
  5. Haws, David; Cussens, James; Studený, Milan: Polyhedral approaches to learning Bayesian networks (2017)
  6. Ichim, Bogdan; Katthän, Lukas; Moyano-Fernández, Julio José: How to compute the Stanley depth of a module (2017)
  7. Khan, Kamil A.; Watson, Harry A.J.; Barton, Paul I.: Differentiable McCormick relaxations (2017)
  8. Puranik, Yash; Sahinidis, Nikolaos V.: Bounds tightening based on optimality conditions for nonconvex box-constrained optimization (2017)
  9. Andreatta, G.; Casula, M.; De Francesco, C.; De Giovanni, L.: A branch-and-price based heuristic for the stochastic vehicle routing problem with hard time windows (2016)
  10. Berthold, Timo; Farmer, James; Heinz, Stefan; Perregaard, Michael: Parallelization of the FICO Xpress-Optimizer (2016)
  11. Borndörfer, Ralf; Schenker, Sebastian; Skutella, Martin; Strunk, Timo: PolySCIP (2016)
  12. Borraz-Sánchez, Conrado; Bent, Russell; Backhaus, Scott; Hijazi, Hassan; Van Hentenryck, Pascal: Convex relaxations for gas expansion planning (2016)
  13. Boukouvala, Fani; Misener, Ruth; Floudas, Christodoulos A.: Global optimization advances in mixed-integer nonlinear programming, MINLP, and constrained derivative-free optimization, CDFO (2016)
  14. Braun, Gábor; Pokutta, Sebastian: A polyhedral characterization of border bases (2016)
  15. Bruns, Winfried; Sieg, Richard; Söger, Christof: The subdivision of large simplicial cones in normaliz (2016)
  16. 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)
  17. Csercsik, Dávid: Lying generators: manipulability of centralized payoff mechanisms in electrical energy trade (2016)
  18. D’Andreagiovanni, Fabio; Gleixner, Ambros M.: Towards an accurate solution of wireless network design problems (2016)
  19. Fischetti, Matteo; Lodi, Andrea; Monaci, Michele; Salvagnin, Domenico; Tramontani, Andrea: Improving branch-and-cut performance by random sampling (2016)
  20. Friberg, Henrik A.: CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization (2016)

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