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 331 articles , 4 standard articles )

Showing results 21 to 40 of 331.
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  1. Gurski, Frank; Rethmann, Jochen: Distributed solving of mixed-integer programs with GLPK and Thrift (2018)
  2. Hiller, Benjamin; Koch, Thorsten; Schewe, Lars; Schwarz, Robert; Schweiger, Jonas: A system to evaluate gas network capacities: concepts and implementation (2018)
  3. Hoppmann, Kai; Schwarz, Robert: Finding maximum minimum cost flows to evaluate gas network capacities (2018)
  4. Kılınç, Mustafa R.; Sahinidis, Nikolaos V.: Exploiting integrality in the global optimization of mixed-integer nonlinear programming problems with BARON (2018)
  5. Kimura, Keiji; Waki, Hayato: Minimization of Akaike’s information criterion in linear regression analysis via mixed integer nonlinear program (2018)
  6. Lancia, Giuseppe; Serafini, Paolo: Compact extended linear programming models (2018)
  7. Lara, Cristiana L.; Trespalacios, Francisco; Grossmann, Ignacio E.: Global optimization algorithm for capacitated multi-facility continuous location-allocation problems (2018)
  8. Le Bodic, Pierre; Pavelka, Jeffrey W.; Pfetsch, Marc E.; Pokutta, Sebastian: Solving MIPs via scaling-based augmentation (2018)
  9. Lee, Jon; Skipper, Daphne; Speakman, Emily: Algorithmic and modeling insights via volumetric comparison of polyhedral relaxations (2018)
  10. Leise, Philipp; Altherr, Lena C.; Pelz, Peter F.: Energy-efficient design of a water supply system for skyscrapers by mixed-integer nonlinear programming (2018)
  11. Lim, Cong Han; Linderoth, Jeff; Luedtke, James: Valid inequalities for separable concave constraints with indicator variables (2018)
  12. Lodi, Andrea; Moradi, Ahmad: Experiments on virtual private network design with concave capacity costs (2018)
  13. López, C. O.; Beasley, J. E.: Packing unequal rectangles and squares in a fixed size circular container using formulation space search (2018)
  14. Lubin, Miles; Yamangil, Emre; Bent, Russell; Vielma, Juan Pablo: Polyhedral approximation in mixed-integer convex optimization (2018)
  15. Malone, Brandon; Kangas, Kustaa; Järvisalo, Matti; Koivisto, Mikko; Myllymäki, Petri: Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction (2018)
  16. Mertens, Nick; Kunde, Christian; Kienle, Achim; Michaels, Dennis: Monotonic reformulation and bound tightening for global optimization of ideal multi-component distillation columns (2018)
  17. Montanher, Tiago; Neumaier, Arnold; Domes, Ferenc: A computational study of global optimization solvers on two trust region subproblems (2018)
  18. Pajor, Thomas; Uchoa, Eduardo; Werneck, Renato F.: A robust and scalable algorithm for the Steiner problem in graphs (2018)
  19. Schweiger, Jonas: Exploiting structure in non-convex quadratic optimization and gas network planning under uncertainty (2018)
  20. Schweiger, Jonas; Liers, Frauke: A decomposition approach for optimal gas network extension with a finite set of demand scenarios (2018)

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