Proximity and Flatness Bounds for Linear Integer Optimization


METADATA ONLY
Loading...

Date

2024-11

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric
METADATA ONLY

Data

Rights / License

Abstract

This paper deals with linear integer optimization. We develop a technique that can be applied to provide improved upper bounds for two important questions in linear integer optimization. Given an optimal vertex solution for the linear relaxation, how far away is the nearest optimal integer solution (if one exists; proximity bounds)? If a polyhedron contains no integer point, what is the smallest number of integer parallel hyperplanes defined by an integral, nonzero, normal vector that intersect the polyhedron (flatness bounds)? This paper presents a link between these two questions by refining a proof technique that has been recently introduced by the authors. A key technical lemma underlying our technique concerns the areas of certain convex polygons in the plane; if a polygon K ⊆ R2 satisfies τK ⊆ K◦, where τ denotes 90◦ counterclockwise rotation and K◦ denotes the polar of K, then the area of K◦ is at least three.

Publication status

published

Editor

Book title

Volume

49 (4)

Pages / Article No.

2446 - 2467

Publisher

INFORMS

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

03873 - Weismantel, Robert / Weismantel, Robert check_circle

Notes

Funding

Related publications and datasets