An Approximation Algorithm for Maximum Internal Spanning Tree View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2017-02-21

AUTHORS

Zhi-Zhong Chen , Youta Harada , Fei Guo , Lusheng Wang

ABSTRACT

Given a graph G, the maximum internal spanning tree problem (MIST for short) asks for computing a spanning tree T of G such that the number of internal vertices in T is maximized. MIST has possible applications in the design of cost-efficient communication networks and water supply networks and hence has been extensively studied in the literature. MIST is NP-hard and hence a number of polynomial-time approximation algorithms have been designed for MIST in the literature. The previously best polynomial-time approximation algorithm for MIST achieves a ratio of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{3}{4}$$\end{document}. In this paper, we first design a simpler algorithm that achieves the same ratio and the same time complexity as the previous best. We then refine the algorithm into a new approximation algorithm that achieves a better ratio (namely, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{13}{17}$$\end{document}) with the same time complexity. Our new algorithm explores much deeper structure of the problem than the previous best. As our recent \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{1}{2}$$\end{document}-approximation algorithm for the weighted version of the problem shows, the discovered structure may be used to design better algorithms for related problems. More... »

PAGES

385-396

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-53925-6_30

DOI

http://dx.doi.org/10.1007/978-3-319-53925-6_30

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1083898580


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