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)


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.


Short Path Line Segment Grid Line Admissible Solution Vertical Line Segment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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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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