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
URI: http://www.orsj.or.jp/ramp/2014/paper/4-4.pdf
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.
APA:
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.
MLA:
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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