Parallel Redundancy Removal in lrslib with Application to Projections
<|reference_start|>Parallel Redundancy Removal in lrslib with Application to Projections: 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.<|reference_end|>
@article{avis2024parallel,
    title={Parallel Redundancy Removal in lrslib with Application to Projections},
    author={David Avis and Charles Jordan},
    journal={arXiv preprint arXiv:2406.00065},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.00065},
    primaryClass={math.OC cs.CG cs.MS}
}