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 268 articles , 4 standard articles )

Showing results 21 to 40 of 268.
Sorted by year (citations)

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  1. Hanafi, Saïd; Todosijević, Raca: Mathematical programming based heuristics for the 0--1 MIP: a survey (2017)
  2. Haws, David; Cussens, James; Studený, Milan: Polyhedral approaches to learning Bayesian networks (2017)
  3. Hendel, Gregor: Exploiting solving phases for mixed-integer programs (2017)
  4. Hijazi, Hassan; Coffrin, Carleton; Van Hentenryck, Pascal: Convex quadratic relaxations for mixed-integer nonlinear programs in power systems (2017)
  5. Humpola, Jesco; Serrano, Felipe: Sufficient pruning conditions for MINLP in gas network design (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. Kruber, Markus; Lübbecke, Marco E.; Parmentier, Axel: Learning when to use a decomposition (2017)
  9. Le Bodic, Pierre; Nemhauser, George: An abstract model for branching and its application to mixed integer programming (2017)
  10. Lee, Jon; Skipper, Daphne: Virtuous smoothing for global optimization (2017)
  11. Lima, Ricardo M.; Grossmann, Ignacio E.: On the solution of nonconvex cardinality Boolean quadratic programming problems: a computational study (2017)
  12. Modaresi, Sina; Vielma, Juan Pablo: Convex hull of two quadratic or a conic quadratic and a quadratic inequality (2017)
  13. Newby, Eric; Ali, M.M.: Linear transformation based solution methods for non-convex mixed integer quadratic programs (2017)
  14. Pčolka, Matej; Čelikovský, Sergej: Production-process optimization algorithm: application to fed-batch bioprocess (2017)
  15. Pecin, Diego; Pessoa, Artur; Poggi, Marcus; Uchoa, Eduardo: Improved branch-cut-and-price for capacitated vehicle routing (2017)
  16. Pferschy, Ulrich; Staněk, Rostislav: Generating subtour elimination constraints for the TSP from pure integer solutions (2017)
  17. Puranik, Yash; Sahinidis, Nikolaos V.: Bounds tightening based on optimality conditions for nonconvex box-constrained optimization (2017)
  18. Toth, Csaba D. (ed.); Goodman, Jacob E. (ed.); O’Rourke, Joseph (ed.): Handbook of discrete and computational geometry (2017)
  19. Umetani, Shunji: Exploiting variable associations to configure efficient local search algorithms in large-scale binary integer programs (2017)
  20. Witzig, Jakob; Berthold, Timo; Heinz, Stefan: Experiments with conflict analysis in mixed integer programming (2017)

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