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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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