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A 1.5-Approximation of the Minimal Manhattan Network Problem

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Algorithms and Computation (ISAAC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3827))

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Abstract

Given a set of points in the plane, the Minimal Manhattan Network Problem asks for an axis-parallel network that connects every pair of points by a shortest path under L 1-norm (Manhattan metric). The goal is to minimize the overall length of the network.

We present an approximation algorithm that provides a solution of length at most 1.5 times the optimum. Previously, the best known algorithm has given only a 2-approximation.

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References

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Author information

Authors and Affiliations

  1. Department Informatik, ETH Zentrum, ETH Zürich, CH-8092, Zürich

    Sebastian Seibert

  2. Lehrstuhl für Informatik I, RWTH Aachen, D-52056, Aachen

    Walter Unger

Authors
  1. Sebastian Seibert
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  2. Walter Unger
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Editor information

Editors and Affiliations

  1. Department of Computer Science, City University of Hong Kong, Tat Chee Avenue, Kowloon , Hong Kong

    Xiaotie Deng

  2. Department of Computer Science, University of Texas at Dallas, EE/CS Building, 75083, Richardson, TX, USA

    Ding-Zhu Du

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© 2005 Springer-Verlag Berlin Heidelberg

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Seibert, S., Unger, W. (2005). A 1.5-Approximation of the Minimal Manhattan Network Problem. In: Deng, X., Du, DZ. (eds) Algorithms and Computation. ISAAC 2005. Lecture Notes in Computer Science, vol 3827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11602613_26

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  • DOI: https://doi.org/10.1007/11602613_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30935-2

  • Online ISBN: 978-3-540-32426-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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