Parallel Redundancy Removal in lrslib with Application to Projections

Fuente: arXiv
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Main Authors: Avis, David, Jordan, Charles
Format: Preprint
Published: 2024
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author Avis, David
Jordan, Charles
author_facet Avis, David
Jordan, Charles
contents We describe a parallel implementation in lrslib for removing redundant halfspaces and finding a minimum representation for an H-representation of a convex polyhedron. By a standard transformation, the same code works for V-representations. We use this approach to speed up the redundancy removal step in Fourier-Motzkin elimination. Computational results are given including a comparison with Clarkson's algorithm, which is particularly fast on highly redundant inputs.
format Preprint
id arxiv_https___arxiv_org_abs_2406_00065
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Parallel Redundancy Removal in lrslib with Application to Projections
Avis, David
Jordan, Charles
Optimization and Control
Computational Geometry
Mathematical Software
We describe a parallel implementation in lrslib for removing redundant halfspaces and finding a minimum representation for an H-representation of a convex polyhedron. By a standard transformation, the same code works for V-representations. We use this approach to speed up the redundancy removal step in Fourier-Motzkin elimination. Computational results are given including a comparison with Clarkson's algorithm, which is particularly fast on highly redundant inputs.
title Parallel Redundancy Removal in lrslib with Application to Projections
topic Optimization and Control
Computational Geometry
Mathematical Software
url https://arxiv.org/abs/2406.00065