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 237 articles , 4 standard articles )

Showing results 41 to 60 of 237.
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  1. Kevin K. H. Cheung, Ambros Gleixner, Daniel E. Steffy: Verifying Integer Programming Results (2016) arXiv
  2. Kimura, Keiji; Waki, Hayato: Mixed integer nonlinear program for minimization of Akaike’s information criterion (2016)
  3. Ku, Wen-Yang; Beck, J.Christopher: Mixed integer programming models for job shop scheduling: A computational analysis (2016)
  4. López, C.O.; Beasley, J.E.: A formulation space search heuristic for packing unequal circles in a fixed size circular container (2016)
  5. Maher, Stephen; Miltenberger, Matthias; Pedroso, João Pedro; Rehfeldt, Daniel; Schwarz, Robert; Serrano, Felipe: PySCIPOpt: mathematical programming in python with the SCIP optimization suite (2016)
  6. Miles Lubin, Emre Yamangil, Russell Bent, Juan Pablo Vielma: Polyhedral approximation in mixed-integer convex optimization (2016) arXiv
  7. Modaresi, Sina; Kılınç, Mustafa R.; Vielma, Juan Pablo: Intersection cuts for nonlinear integer programming: convexification techniques for structured sets (2016)
  8. Newby, Eric; Ali, M.Montaz: Transformation-based preprocessing for mixed-integer quadratic programs (2016)
  9. Oates, Chris.J.; Smith, Jim Q.; Mukherjee, Sach: Estimating causal structure using conditional DAG models (2016)
  10. Oates, Chris J.; Smith, Jim Q.; Mukherjee, Sach; Cussens, James: Exact estimation of multiple directed acyclic graphs (2016)
  11. Oren, Yossef; Wool, Avishai: Side-channel cryptographic attacks using pseudo-Boolean optimization (2016)
  12. Rose, Daniel; Schmidt, Martin; Steinbach, Marc C.; Willert, Bernhard M.: Computational optimization of gas compressor stations: MINLP models versus continuous reformulations (2016)
  13. Saikko, Paul; Berg, Jeremias; Järvisalo, Matti: LMHS: A SAT-IP hybrid maxsat solver (2016)
  14. Salvagnin, Domenico: Detecting semantic groups in MIP models (2016)
  15. Schnell, Alexander; Hartl, Richard F.: On the efficient modeling and solution of the multi-mode resource-constrained project scheduling problem with generalized precedence relations (2016)
  16. Shinano, Yuji; Berthold, Timo; Heinz, Stefan: A first implementation of paraxpress: combining internal and external parallelization to solve MIPs on supercomputers (2016)
  17. Tran, Tony T.; Araujo, Arthur; Beck, J.Christopher: Decomposition methods for the parallel machine scheduling problem with setups (2016)
  18. Zhang, Yan; Sahinidis, Nikolaos V.: Global optimization of mathematical programs with complementarity constraints and application to clean energy deployment (2016)
  19. Abe, Fabio Henrique N.; Hoshino, Edna A.; Hill, Alessandro: The ring tree facility location problem (2015)
  20. Berthold, Timo; Hendel, Gregor: Shift-and-propagate (2015)

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