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preprint

Complexity of linear relaxations in integer programming

Averkov, Gennadiy
•
Schymura, Matthias  
March 17, 2020

For a set X of integer points in a polyhedron, the smallest number of facets of any polyhedron whose set of integer points coincides with X is called the relaxation complexity rc(X). This parameter was introduced by Kaibel & Weltge (2015) and captures the complexity of linear descriptions of X without using auxiliary variables. Using tools from combinatorics, geometry of numbers, and quantifier elimination, we make progress on several open questions regarding rc(X) and its variant rcℚ(X), restricting the descriptions of X to rational polyhedra. As our main results we show that rc(X)=rcℚ(X) when: (a) X is at most four-dimensional, (b) X represents every residue class in (ℤ/2ℤ)d, (c) the convex hull of X contains an interior integer point, or (d) the lattice-width of X is above a certain threshold. Additionally, rc(X) can be algorithmically computed when X is at most three-dimensional, or X satisfies one of the conditions (b), (c), or (d) above. Moreover, we obtain an improved lower bound on rc(X) in terms of the dimension of X.

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Type
preprint
ArXiv ID

2003.07817

Author(s)
Averkov, Gennadiy
Schymura, Matthias  
Date Issued

2020-03-17

Editorial or Peer reviewed

NON-REVIEWED

Written at

EPFL

EPFL units
DISOPT  
FunderGrant Number

FNS

185030

Available on Infoscience
March 27, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/167693
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