Tuesday, 15:45 - 16:10 h, Room: MA 005


Jeff Linderoth
Solving mixed integer polynomial optimization problems with MINOTAUR

Coauthors: Jim Luedtke, Ashutosh Mahajan, Mahdi Namazifar


We study methods for building polyhedral relaxations of multilinear
terms that arise in nonconvex mixed integer optimization problems.
The goal is to obtain a formulation that is more compact than the
convex hull formulation, but yields tighter relaxations than the
standard McCormick relaxation. We present computational results for an
approach based on grouping the variables into subsets that cover all
multilinear terms in the problem. The approach is combined with
additional reformulation techniques and spatial branching in the
software framework MINOTAUR to produce a solver for mixed integer
polynomial optimization problems.


Talk 2 of the invited session Tue.3.MA 005
"Convex relaxations for nonconvex optimization problems" [...]
Cluster 14
"Mixed-integer nonlinear programming" [...]


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