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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2111.09290 |
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| _version_ | 1866915391293358080 |
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| author | Gupta, Anupam Lee, Euiwoong Li, Jason Mucha, Marcin Newman, Heather Sarkar, Sherry |
| author_facet | Gupta, Anupam Lee, Euiwoong Li, Jason Mucha, Marcin Newman, Heather Sarkar, Sherry |
| contents | We show how to round any half-integral solution to the subtour-elimination relaxation for the TSP, while losing a less-than-1.5 factor. Such a rounding algorithm was recently given by Karlin, Klein, and Oveis Gharan based on sampling from max-entropy distributions. We build on an approach of Haddadan and Newman to show how sampling from the matroid intersection polytope, and a new use of max-entropy sampling, can give better guarantees. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2111_09290 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Matroid-Based TSP Rounding for Half-Integral Solutions Gupta, Anupam Lee, Euiwoong Li, Jason Mucha, Marcin Newman, Heather Sarkar, Sherry Data Structures and Algorithms We show how to round any half-integral solution to the subtour-elimination relaxation for the TSP, while losing a less-than-1.5 factor. Such a rounding algorithm was recently given by Karlin, Klein, and Oveis Gharan based on sampling from max-entropy distributions. We build on an approach of Haddadan and Newman to show how sampling from the matroid intersection polytope, and a new use of max-entropy sampling, can give better guarantees. |
| title | Matroid-Based TSP Rounding for Half-Integral Solutions |
| topic | Data Structures and Algorithms |
| url | https://arxiv.org/abs/2111.09290 |