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Safe bounds in linear and mixed-integer linear programming
Authors:Arnold Neumaier  Oleg Shcherbina
Institution:(1) Institut für Mathematik, Universität Wien, Strudlhofgasse 4, A-1090 Wien, Austria
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. Mathematics Subject Classification (2000):enspprimary 90C11, secondary 65G20
Keywords:linear programming  mixed-integer programming  rounding errors  directed rounding  interval arithmetic  branch-and-cut  lower bounds  mixed-integer rounding  generalized Gomory cut  safe cuts  safe presolve  certificate of infeasibility
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