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Global optimization of mixed-integer nonlinear programs with SCIP 8

Author

Listed:
  • Ksenia Bestuzheva

    (Zuse Institute Berlin)

  • Antonia Chmiela

    (Zuse Institute Berlin)

  • Benjamin Müller

    (Zuse Institute Berlin)

  • Felipe Serrano

    (Zuse Institute Berlin)

  • Stefan Vigerske

    (c/o Zuse Institute Berlin)

  • Fabian Wegscheider

    (Zuse Institute Berlin)

Abstract

For over 10 years, the constraint integer programming framework SCIP has been extended by capabilities for the solution of convex and nonconvex mixed-integer nonlinear programs (MINLPs). With the recently published version 8.0, these capabilities have been largely reworked and extended. This paper discusses the motivations for recent changes and provides an overview of features that are particular to MINLP solving in SCIP. Further, difficulties in benchmarking global MINLP solvers are discussed and a comparison with several state-of-the-art global MINLP solvers is provided.

Suggested Citation

  • Ksenia Bestuzheva & Antonia Chmiela & Benjamin Müller & Felipe Serrano & Stefan Vigerske & Fabian Wegscheider, 2025. "Global optimization of mixed-integer nonlinear programs with SCIP 8," Journal of Global Optimization, Springer, vol. 91(2), pages 287-310, February.
    • Handle: RePEc:spr:jglopt:v:91:y:2025:i:2:d:10.1007_s10898-023-01345-1
    DOI: 10.1007/s10898-023-01345-1
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    References listed on IDEAS

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    1. Arthur F. Veinott, 1967. "The Supporting Hyperplane Method for Unimodal Programming," Operations Research, INFORMS, vol. 15(1), pages 147-152, February.
    2. Ambros M. Gleixner & Timo Berthold & Benjamin Müller & Stefan Weltge, 2017. "Three enhancements for optimization-based bound tightening," Journal of Global Optimization, Springer, vol. 67(4), pages 731-757, April.
    3. Pierre Hansen & Brigitte Jaumard & MichèLe Ruiz & Junjie Xiong, 1993. "Global minimization of indefinite quadratic functions subject to box constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(3), pages 373-392, April.
    4. Marco Locatelli, 2018. "Convex envelopes of bivariate functions through the solution of KKT systems," Journal of Global Optimization, Springer, vol. 72(2), pages 277-303, October.
    5. Laurence Smith & John Chinneck & Victor Aitken, 2013. "Improved constraint consensus methods for seeking feasibility in nonlinear programs," Computational Optimization and Applications, Springer, vol. 54(3), pages 555-578, April.
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