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 486 articles , 4 standard articles )

Showing results 1 to 20 of 486.
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  1. Antoine Prouvost, Justin Dumouchelle, Maxime Gasse, Didier Chételat, Andrea Lodi: Ecole: A Library for Learning Inside MILP Solvers (2021) arXiv
  2. Bendotti, Pascale; Fouilhoux, Pierre; Rottner, Cécile: Orbitopal fixing for the full (sub-)orbitope and application to the unit commitment problem (2021)
  3. Berthold, Timo; Witzig, Jakob: Conflict analysis for MINLP (2021)
  4. Blanco, V.; Japón, A.; Ponce, D.; Puerto, J.: On the multisource hyperplanes location problem to fitting set of points (2021)
  5. Casazza, Marco; Ceselli, Alberto: Optimization algorithms for resilient path selection in networks (2021)
  6. Casazza, Marco; Ceselli, Alberto; Wolfler Calvo, Roberto: A route decomposition approach for the single commodity split pickup and split delivery vehicle routing problem (2021)
  7. Çelik, Türkü Özlüm; Jamneshan, Asgar; Montúfar, Guido; Sturmfels, Bernd; Venturello, Lorenzo: Wasserstein distance to independence models (2021)
  8. 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)
  9. Dias, Gustavo; Liberti, Leo: Exploiting symmetries in mathematical programming via orbital independence (2021)
  10. Lübbecke, Marco E.; Maher, Stephen J.; Witt, Jonas T.: Avoiding redundant columns by adding classical Benders cuts to column generation subproblems (2021)
  11. Maher, Stephen J.: Implementing the branch-and-cut approach for a general purpose Benders’ decomposition framework (2021)
  12. Mezőfi, Dávid; Nagy, Gábor P.: New Steiner 2-designs from old ones by paramodifications (2021)
  13. Okuno, Takayuki; Ikebe, Yoshiko: A new approach for solving mixed integer DC programs using a continuous relaxation with no integrality gap and smoothing techniques (2021)
  14. Sundar, Kaarthik; Nagarajan, Harsha; Linderoth, Jeff; Wang, Site; Bent, Russell: Piecewise polyhedral formulations for a multilinear term (2021)
  15. Witzig, Jakob; Gleixner, Ambros: Conflict-driven heuristics for mixed integer programming (2021)
  16. Wolsey, Laurence A.: Integer programming (2021)
  17. Achterberg, Tobias; Bixby, Robert E.; Gu, Zonghao; Rothberg, Edward; Weninger, Dieter: Presolve reductions in mixed integer programming (2020)
  18. Aleksander Figiel, Anne-Sophie Himmel, Andre Nichterlein, Rolf Niedermeier: On 2-Clubs in Graph-Based Data Clustering: Theory and Algorithm Engineering (2020) arXiv
  19. Alimo, Ryan; Beyhaghi, Pooriya; Bewley, Thomas R.: Delaunay-based derivative-free optimization via global surrogates. III: nonconvex constraints (2020)
  20. Basso, S.; Ceselli, Alberto; Tettamanzi, Andrea: Random sampling and machine learning to understand good decompositions (2020)

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