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Main Authors: Gupta, Anupam, Lee, Euiwoong, Li, Jason, Mucha, Marcin, Newman, Heather, Sarkar, Sherry
Format: Preprint
Published: 2021
Subjects:
Online Access:https://arxiv.org/abs/2111.09290
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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