Backing PDHG into a Corner

Fuente: arXiv
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Autor principal: Rothberg, Edward
Formato: Preprint
Publicado: 2025
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author Rothberg, Edward
author_facet Rothberg, Edward
contents Recent enhancements to the Primal-Dual Hybrid Gradient (PDHG) algorithm have enabled GPUs to efficiently solve large linear programming problems, often faster than the long-dominant simplex and interior-point methods. The solutions found by PDHG are typically of much lower quality than those found by the alternatives, which can be remedied by following the PDHG iterations with a crossover step to obtain an accurate optimal basic solution. However, the cost of this highly sequential crossover step can be quite significant. This paper examines whether PDHG iterations can be enhanced to push the solution into a corner of the optimal LP face, thereby providing crossover a better starting point and hopefully reducing its runtime.
format Preprint
id arxiv_https___arxiv_org_abs_2511_13894
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Backing PDHG into a Corner
Rothberg, Edward
Optimization and Control
Recent enhancements to the Primal-Dual Hybrid Gradient (PDHG) algorithm have enabled GPUs to efficiently solve large linear programming problems, often faster than the long-dominant simplex and interior-point methods. The solutions found by PDHG are typically of much lower quality than those found by the alternatives, which can be remedied by following the PDHG iterations with a crossover step to obtain an accurate optimal basic solution. However, the cost of this highly sequential crossover step can be quite significant. This paper examines whether PDHG iterations can be enhanced to push the solution into a corner of the optimal LP face, thereby providing crossover a better starting point and hopefully reducing its runtime.
title Backing PDHG into a Corner
topic Optimization and Control
url https://arxiv.org/abs/2511.13894