Hybridizing PDHG and Interior-Point Methods
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917310390861824 |
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| author | Rothberg, Edward |
| author_facet | Rothberg, Edward |
| contents | The Primal-Dual Hybrid Gradient (PDHG) algorithm is a first-order method that can exploit GPUs to solve large-scale linear programming problems. The approach can often be faster than the alternatives, simplex and interior-point methods, typically at the cost of much lower accuracy. This paper looks at whether PDHG can be hybridized with an interior-point method to retain some of the speed advantages of the former while capturing the accuracy advantages of the latter. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_03150 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Hybridizing PDHG and Interior-Point Methods Rothberg, Edward Optimization and Control The Primal-Dual Hybrid Gradient (PDHG) algorithm is a first-order method that can exploit GPUs to solve large-scale linear programming problems. The approach can often be faster than the alternatives, simplex and interior-point methods, typically at the cost of much lower accuracy. This paper looks at whether PDHG can be hybridized with an interior-point method to retain some of the speed advantages of the former while capturing the accuracy advantages of the latter. |
| title | Hybridizing PDHG and Interior-Point Methods |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2603.03150 |