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 472 articles , 4 standard articles )

Showing results 1 to 20 of 472.
Sorted by year (citations)

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  1. Ceselli, Alberto; Felipe, Ángel; Ortuño, M. Teresa; Righini, Giovanni; Tirado, Gregorio: A branch-and-cut-and-price algorithm for the electric vehicle routing problem with multiple technologies (2021)
  2. Mezőfi, Dávid; Nagy, Gábor P.: New Steiner 2-designs from old ones by paramodifications (2021)
  3. Wolsey, Laurence A.: Integer programming (2021)
  4. Achterberg, Tobias; Bixby, Robert E.; Gu, Zonghao; Rothberg, Edward; Weninger, Dieter: Presolve reductions in mixed integer programming (2020)
  5. Aleksander Figiel, Anne-Sophie Himmel, Andre Nichterlein, Rolf Niedermeier: On 2-Clubs in Graph-Based Data Clustering: Theory and Algorithm Engineering (2020) arXiv
  6. Alimo, Ryan; Beyhaghi, Pooriya; Bewley, Thomas R.: Delaunay-based derivative-free optimization via global surrogates. III: nonconvex constraints (2020)
  7. Basso, S.; Ceselli, Alberto; Tettamanzi, Andrea: Random sampling and machine learning to understand good decompositions (2020)
  8. Benadè, Gerdus; Hooker, John N.: Optimization bounds from the branching dual (2020)
  9. Bogdanov, I. P.; Sudakov, V. A.; Toporov, N. B.: Loading optimization of an ordered set of aircrafts (2020)
  10. Bulhões, Teobaldo; Sadykov, Ruslan; Subramanian, Anand; Uchoa, Eduardo: On the exact solution of a large class of parallel machine scheduling problems (2020)
  11. Burlacu, Robert; Geißler, Björn; Schewe, Lars: Solving mixed-integer nonlinear programmes using adaptively refined mixed-integer linear programmes (2020)
  12. Coey, Chris; Lubin, Miles; Vielma, Juan Pablo: Outer approximation with conic certificates for mixed-integer convex problems (2020)
  13. Deleplanque, Samuel; Labbé, Martine; Ponce, Diego; Puerto, Justo: A branch-price-and-cut procedure for the discrete ordered Median problem (2020)
  14. Del Pia, Alberto; Khajavirad, Aida; Sahinidis, Nikolaos V.: On the impact of running intersection inequalities for globally solving polynomial optimization problems (2020)
  15. De Santis, Marianna; Eichfelder, Gabriele; Niebling, Julia; Rocktäschel, Stefan: Solving multiobjective mixed integer convex optimization problems (2020)
  16. Enayati, Shakiba; Özaltın, Osman Y.: Optimal influenza vaccine distribution with equity (2020)
  17. Fischer, Tobias; Pfetsch, Marc E.: On the structure of linear programs with overlapping cardinality constraints (2020)
  18. Fischetti, Matteo; Monaci, Michele: A branch-and-cut algorithm for mixed-integer bilinear programming (2020)
  19. Gamrath, Gerald; Berthold, Timo; Salvagnin, Domenico: An exploratory computational analysis of dual degeneracy in mixed-integer programming (2020)
  20. Garvie, Marcus; Burkardt, John: A new mathematical model for tiling finite regions of the plane with polyominoes (2020)

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