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 426 articles , 4 standard articles )

Showing results 1 to 20 of 426.
Sorted by year (citations)

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  1. Aleksander Figiel, Anne-Sophie Himmel, Andre Nichterlein, Rolf Niedermeier: On 2-Clubs in Graph-Based Data Clustering: Theory and Algorithm Engineering (2020) arXiv
  2. Basso, S.; Ceselli, Alberto; Tettamanzi, Andrea: Random sampling and machine learning to understand good decompositions (2020)
  3. Bogdanov, I. P.; Sudakov, V. A.; Toporov, N. B.: Loading optimization of an ordered set of aircrafts (2020)
  4. Enayati, Shakiba; Özaltın, Osman Y.: Optimal influenza vaccine distribution with equity (2020)
  5. Fischer, Tobias; Pfetsch, Marc E.: On the structure of linear programs with overlapping cardinality constraints (2020)
  6. Fischetti, Matteo; Monaci, Michele: A branch-and-cut algorithm for mixed-integer bilinear programming (2020)
  7. Gleixner, Ambros; Maher, Stephen J.; Müller, Benjamin; Pedroso, João Pedro: Price-and-verify: a new algorithm for recursive circle packing using Dantzig-Wolfe decomposition (2020)
  8. Grimstad, Bjarne; Knudsen, Brage R.: Mathematical programming formulations for piecewise polynomial functions (2020)
  9. Izunaga, Yoichi; Matsui, Tomomi; Yamamoto, Yoshitsugu: A doubly nonnegative relaxation for modularity density maximization (2020)
  10. Kazachkov, Aleksandr M.; Nadarajah, Selvaprabu; Balas, Egon; Margot, François: Partial hyperplane activation for generalized intersection cuts (2020)
  11. Kobayashi, Ken; Takano, Yuich: A branch-and-cut algorithm for solving mixed-integer semidefinite optimization problems (2020)
  12. Müller, Benjamin; Serrano, Felipe; Gleixner, Ambros: Using two-dimensional projections for stronger separation and propagation of bilinear terms (2020)
  13. Muts, Pavlo; Nowak, Ivo; Hendrix, Eligius M. T.: The decomposition-based outer approximation algorithm for convex mixed-integer nonlinear programming (2020)
  14. Pedroso, João Pedro: Heuristics for packing semifluids (2020)
  15. Pulaj, Jonad: Cutting planes for families implying Frankl’s conjecture (2020)
  16. Sebastiani, Roberto; Trentin, Patrick: \textscOptiMathSAT: a tool for optimization modulo theories (2020)
  17. Yamamura, Kiyotaka: Finding all solution sets of piecewise-linear interval equations using an integer programming solver (2020)
  18. Zhang, Yi; Sahinidis, Nikolaos V.; Nohra, Carlos; Rong, Gang: Optimality-based domain reduction for inequality-constrained NLP and MINLP problems (2020)
  19. Altherr, Lena C.; Leise, Philipp; Pfetsch, Marc E.; Schmitt, Andreas: Resilient layout, design and operation of energy-efficient water distribution networks for high-rise buildings using MINLP (2019)
  20. Bagger, Niels-Christian Fink; Desaulniers, Guy; Desrosiers, Jacques: Daily course pattern formulation and valid inequalities for the curriculum-based course timetabling problem (2019)

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