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 536 articles , 4 standard articles )

Showing results 41 to 60 of 536.
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  1. Kobayashi, Ken; Takano, Yuichi; Nakata, Kazuhide: Bilevel cutting-plane algorithm for cardinality-constrained mean-CVaR portfolio optimization (2021)
  2. Liers, Frauke; Martin, Alexander; Merkert, Maximilian; Mertens, Nick; Michaels, Dennis: Solving mixed-integer nonlinear optimization problems using simultaneous convexification: a case study for gas networks (2021)
  3. Lübbecke, Marco E.; Maher, Stephen J.; Witt, Jonas T.: Avoiding redundant columns by adding classical Benders cuts to column generation subproblems (2021)
  4. Mahajan, Ashutosh; Leyffer, Sven; Linderoth, Jeff; Luedtke, James; Munson, Todd: Minotaur: a mixed-integer nonlinear optimization toolkit (2021)
  5. Maher, Stephen J.: Implementing the branch-and-cut approach for a general purpose Benders’ decomposition framework (2021)
  6. Martin, Florian; Hemmelmayr, Vera C.; Wakolbinger, Tina: Integrated express shipment service network design with customer choice and endogenous delivery time restrictions (2021)
  7. Mazyavkina, Nina; Sviridov, Sergey; Ivanov, Sergei; Burnaev, Evgeny: Reinforcement learning for combinatorial optimization: a survey (2021)
  8. Mezőfi, Dávid; Nagy, Gábor P.: New Steiner 2-designs from old ones by paramodifications (2021)
  9. Mihić, Krešimir; Zhu, Mingxi; Ye, Yinyu: Managing randomization in the multi-block alternating direction method of multipliers for quadratic optimization (2021)
  10. Muts, Pavlo; Nowak, Ivo; Hendrix, Eligius M. T.: On decomposition and multiobjective-based column and disjunctive cut generation for MINLP (2021)
  11. Najman, Jaromił; Bongartz, Dominik; Mitsos, Alexander: Linearization of McCormick relaxations and hybridization with the auxiliary variable method (2021)
  12. Neumann, Christoph; Stein, Oliver: Generating feasible points for mixed-integer convex optimization problems by inner parallel cuts (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. Rössig, Ansgar; Petkovic, Milena: Advances in verification of ReLU neural networks (2021)
  15. Schweidtmann, Artur M.; Bongartz, Dominik; Grothe, Daniel; Kerkenhoff, Tim; Lin, Xiaopeng; Najman, Jaromił; Mitsos, Alexander: Deterministic global optimization with Gaussian processes embedded (2021)
  16. Sharma, Meenarli; Hahn, Mirko; Leyffer, Sven; Ruthotto, Lars; van Bloemen Waanders, Bart: Inversion of convection-diffusion equation with discrete sources (2021)
  17. Sundar, Kaarthik; Nagarajan, Harsha; Linderoth, Jeff; Wang, Site; Bent, Russell: Piecewise polyhedral formulations for a multilinear term (2021)
  18. Tjandraatmadja, Christian; van Hoeve, Willem-Jan: Incorporating bounds from decision diagrams into integer programming (2021)
  19. Vasallo, Manuel Jesús; Cojocaru, Emilian Gelu; Gegúndez, Manuel Emilio; Marín, Diego: Application of data-based solar field models to optimal generation scheduling in concentrating solar power plants (2021)
  20. Wang, Akang; Gounaris, Chrysanthos E.: On tackling reverse convex constraints for non-overlapping of unequal circles (2021)

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Further publications can be found at: