Preprocessing techniques for discrete optimization problems

Wednesday, November 19, 2008 - 2:45pm - 3:10pm
EE/CS 3-180
Todd Munson (Argonne National Laboratory)
Preprocessing technique simplify and strengthen a model prior to calculating a solution. A combination of rules exploiting the constraint set and primal-dual relationships are applied to fix variables, improve their bounds, and eliminate redundant expressions. In addition, some nonconvex constraints can be transformed into convex constraints. Exploiting discrete variables during preprocessing adds rules to identify and exploit special structures and strengthen the formulation prior to computing convex estimators and cuts, and exploring a branch-and-bound tree. In this talk, I will discusses a unified preprocessor for mixed integer mathematical programs with equilibrium constraints being developed for MINOTAUR.
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