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Exploring the Numerics of Branch-and-Cut for Mixed Integer Linear Optimization

In: Operations Research Proceedings 2017

Author

Listed:
  • Matthias Miltenberger

    (Zuse Institute Berlin)

  • Ted Ralphs

    (Lehigh University)

  • Daniel E. Steffy

    (Oakland University)

Abstract

We investigate how the numerical properties of the LP relaxations evolve throughout the solution procedure in a solver employing the branch-and-cut algorithm. The long-term goal of this work is to determine whether the effect on the numerical conditioning of the LP relaxations resulting from the branching and cutting operations can be effectively predicted and whether such predictions can be used to make better algorithmic choices. In a first step towards this goal, we discuss here the numerical behavior of an existing solver in order to determine whether our intuitive understanding of this behavior is correct.

Suggested Citation

  • Matthias Miltenberger & Ted Ralphs & Daniel E. Steffy, 2018. "Exploring the Numerics of Branch-and-Cut for Mixed Integer Linear Optimization," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 151-157, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-89920-6_21
    DOI: 10.1007/978-3-319-89920-6_21
    as

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