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 398 articles , 4 standard articles )

Showing results 1 to 20 of 398.
Sorted by year (citations)

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  1. 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)
  2. Baumgartner, János; Süle, Zoltán; Bertók, Botond; Abonyi, János: Test-sequence optimisation by survival analysis (2019)
  3. Bei, Xiaoqiang; Zhu, Xiaoyan; Coit, David W.: A risk-averse stochastic program for integrated system design and preventive maintenance planning (2019)
  4. Bilias, Yannis; Florios, Kostas; Skouras, Spyros: Exact computation of censored least absolute deviations estimator (2019)
  5. Bojarski, Jacek; Kisielewicz, Andrzej Piotr; Przesławski, Krzysztof: Nearly neighbourly families of standard boxes (2019)
  6. Burlacu, Robert; Egger, Herbert; Groß, Martin; Martin, Alexander; Pfetsch, Marc E.; Schewe, Lars; Sirvent, Mathias; Skutella, Martin: Maximizing the storage capacity of gas networks: a global MINLP approach (2019)
  7. Cao, Yankai; Zavala, Victor M.: A scalable global optimization algorithm for stochastic nonlinear programs (2019)
  8. Casazza, Marco: New formulations for variable cost and size bin packing problems with item fragmentation (2019)
  9. Costa, Lilia; Smith, James Q.; Nichols, Thomas: A group analysis using the multiregression dynamic models for fMRI networked time series (2019)
  10. D’Ambrosio, Claudia; Frangioni, Antonio; Gentile, Claudio: Strengthening the sequential convex MINLP technique by perspective reformulations (2019)
  11. Dey, Santanu S.; Santana, Asteroide; Wang, Yang: New SOCP relaxation and branching rule for bipartite bilinear programs (2019)
  12. Elloumi, Sourour; Lambert, Amélie: Global solution of non-convex quadratically constrained quadratic programs (2019)
  13. Furini, Fabio; Traversi, Emiliano; Belotti, Pietro; Frangioni, Antonio; Gleixner, Ambros; Gould, Nick; Liberti, Leo; Lodi, Andrea; Misener, Ruth; Mittelmann, Hans; Sahinidis, Nikolaos V.; Vigerske, Stefan; Wiegele, Angelika: QPLIB: a library of quadratic programming instances (2019)
  14. García-Sánchez, Pedro A.; O’Neill, Christopher; Webb, Gautam: The computation of factorization invariants for affine semigroups (2019)
  15. Grimm, Veronika; Kleinert, Thomas; Liers, Frauke; Schmidt, Martin; Zöttl, Gregor: Optimal price zones of electricity markets: a mixed-integer multilevel model and global solution approaches (2019)
  16. Habeck, Oliver; Pfetsch, Marc E.; Ulbrich, Stefan: Global optimization of mixed-integer ODE constrained network problems using the example of stationary gas transport (2019)
  17. Hojny, Christopher; Pfetsch, Marc E.: Polytopes associated with symmetry handling (2019)
  18. Horváth, Markó; Kis, Tamás: Computing strong lower and upper bounds for the integrated multiple-depot vehicle and crew scheduling problem with branch-and-price (2019)
  19. Keiji, Kimura: Application of a mixed integer nonlinear programming approach to variable selection in logistic regression (2019)
  20. Knust, Frederik; Xie, Lin: Simulated annealing approach to nurse rostering benchmark and real-world instances (2019)

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