Safe bounds in linear and mixed-integer linear programming

  • Authors:
  • Arnold Neumaier;Oleg Shcherbina

  • Affiliations:
  • Universität Wien, Institut für Mathematik, Austria;Universität Wien, Institut für Mathematik, Austria

  • Venue:
  • Mathematical Programming: Series A and B
  • Year:
  • 2004

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Abstract

Current mixed-integer linear programming solvers are based on linear programming routines that use floating-point arithmetic. Occasionally, this leads to wrong solutions, even for problems where all coefficients and all solution components are small integers. An example is given where many state-of-the-art MILP solvers fail. It is then shown how, using directed rounding and interval arithmetic, cheap pre- and postprocessing of the linear programs arising in a branch-and-cut framework can guarantee that no solution is lost, at least for mixed-integer programs in which all variables can be bounded rigorously by bounds of reasonable size.