Graph Threading

Fuente: arXiv
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Bibliographic Details
Main Authors: Demaine, Erik D., Kirkpatrick, Yael, Lin, Rebecca
Format: Preprint
Published: 2023
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author Demaine, Erik D.
Kirkpatrick, Yael
Lin, Rebecca
author_facet Demaine, Erik D.
Kirkpatrick, Yael
Lin, Rebecca
contents Inspired by artistic practices such as beadwork and himmeli, we study the problem of threading a single string through a set of tubes, so that pulling the string forms a desired graph. More precisely, given a connected graph (where edges represent tubes and vertices represent junctions where they meet), we give a polynomial-time algorithm to find a minimum-length closed walk (representing a threading of string) that induces a connected graph of string at every junction. The algorithm is based on a surprising reduction to minimum-weight perfect matching. Along the way, we give tight worst-case bounds on the length of the optimal threading and on the maximum number of times this threading can visit a single edge. We also give more efficient solutions to two special cases: cubic graphs and the case when each edge can be visited at most twice.
format Preprint
id arxiv_https___arxiv_org_abs_2309_10122
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Graph Threading
Demaine, Erik D.
Kirkpatrick, Yael
Lin, Rebecca
Data Structures and Algorithms
G.2.2; F.2.2
Inspired by artistic practices such as beadwork and himmeli, we study the problem of threading a single string through a set of tubes, so that pulling the string forms a desired graph. More precisely, given a connected graph (where edges represent tubes and vertices represent junctions where they meet), we give a polynomial-time algorithm to find a minimum-length closed walk (representing a threading of string) that induces a connected graph of string at every junction. The algorithm is based on a surprising reduction to minimum-weight perfect matching. Along the way, we give tight worst-case bounds on the length of the optimal threading and on the maximum number of times this threading can visit a single edge. We also give more efficient solutions to two special cases: cubic graphs and the case when each edge can be visited at most twice.
title Graph Threading
topic Data Structures and Algorithms
G.2.2; F.2.2
url https://arxiv.org/abs/2309.10122