Parallel Redundancy Removal in lrslib with Application to Projections
Optimization and Control
2024-06-04 v1 Computational Geometry
Mathematical Software
Abstract
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.
Keywords
Cite
@article{arxiv.2406.00065,
title = {Parallel Redundancy Removal in lrslib with Application to Projections},
author = {David Avis and Charles Jordan},
journal= {arXiv preprint arXiv:2406.00065},
year = {2024}
}