5889
2016
eng
449
464
3
28
article
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Iterative Refinement for Linear Programming
We describe an iterative refinement procedure for computing extended precision or exact solutions to linear programming problems (LPs). Arbitrarily precise solutions can be computed by solving a sequence of closely related LPs with limited precision arithmetic. The LPs solved share the same constraint matrix as the original problem instance and are transformed only by modification of the objective function, right-hand side, and variable bounds. Exact computation is used to compute and store the exact representation of the transformed problems, while numeric computation is used for solving LPs. At all steps of the algorithm the LP bases encountered in the transformed problems correspond directly to LP bases in the original problem description. We show that this algorithm is effective in practice for computing extended precision solutions and that it leads to a direct improvement of the best known methods for solving LPs exactly over the rational numbers. Our implementation is publically available as an extension of the academic LP solver SoPlex.
INFORMS Journal on Computing
10.1287/ijoc.2016.0692
yes
urn:nbn:de:0297-zib-55118
Ambros Gleixner
Ambros Gleixner
Daniel Steffy
Kati Wolter
Mathematical Optimization
Mathematical Optimization Methods
Gleixner, Ambros
ASTfSCM
MIP-ZIBOPT
MODAL-SynLab
Siemens
MODAL-Gesamt