Multi-Row Presolve Reductions in Mixed Integer Programming

Achterberg T, Bixby RE, Gu Z, Rothberg E, Weninger D (2014)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2014

Pages Range: 181-196

Conference Proceedings Title: Proceedings of the Twenty-Sixth RAMP Symposium

Event location: Tokyo



Mixed integer programming has become a very powerful tool for modeling and solving real-world planning and scheduling problems, with the breadth of applications appearing to be almost unlimited. A critical component in the solution of these mixed-integer programs is a set of routines commonly referred to as presolve. Presolve can be viewed as a collection of preprocessing techniques that reduce the size of and, more importantly, improve the “strength” of the given model formulation, that is, the degree to which the constraints of the formulation accurately describe the underlying polyhedron of integer-feasible solutions. In the Gurobi commercial mixed-integer solver, the presolve functionality has been steadily enhanced over time, now including a number of so-called multi-row reductions. These are reductions that simultaneously consider multiple constraints to derive improvements in the model formulation. In this paper we give an overview of such multi-row techniques and present computational results to assess their impact on overall solver performance.

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How to cite


Achterberg, T., Bixby, R.E., Gu, Z., Rothberg, E., & Weninger, D. (2014). Multi-Row Presolve Reductions in Mixed Integer Programming. In Hosei University, Tokyo (Eds.), Proceedings of the Twenty-Sixth RAMP Symposium (pp. 181-196). Tokyo.


Achterberg, Tobias, et al. "Multi-Row Presolve Reductions in Mixed Integer Programming." Proceedings of the Twenty-Sixth RAMP Symposium, Tokyo Ed. Hosei University, Tokyo, 2014. 181-196.

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