A 1.5-Approximation of the Minimal Manhattan Network Problem

  • Sebastian Seibert
  • Walter Unger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3827)

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 L1-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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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sebastian Seibert
    • 1
  • Walter Unger
    • 2
  1. 1.Department Informatik, ETH ZentrumETH ZürichZürich
  2. 2.Lehrstuhl für Informatik IRWTH AachenAachen

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