Approximating Minimum Manhattan Networks in Higher Dimensions

  • Aparna Das
  • Emden R. Gansner
  • Michael Kaufmann
  • Stephen Kobourov
  • Joachim Spoerhase
  • Alexander Wolff
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6942)


We consider the minimum Manhattan network problem, which is defined as follows. Given a set of points called terminals in ℝ d , find a minimum-length network such that each pair of terminals is connected by a set of axis-parallel line segments whose total length is equal to the pair’s Manhattan (that is, L 1-) distance. The problem is NP-hard in 2D and there is no PTAS for 3D (unless \({\cal P}\!=\!{\cal NP}\)). Approximation algorithms are known for 2D, but not for 3D.

We present, for any fixed dimension d and any \(\ensuremath{\varepsilon} >0\), an \(O(n^\ensuremath{\varepsilon} )\)-approximation. For 3D, we also give a 4(k − 1)-approximation for the case that the terminals are contained in the union of k ≥ 2 parallel planes.


Approximation Algorithm Approximation Ratio Full Version Vertical Line Segment Grid Algorithm 
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 2011

Authors and Affiliations

  • Aparna Das
    • 1
  • Emden R. Gansner
    • 2
  • Michael Kaufmann
    • 3
  • Stephen Kobourov
    • 1
  • Joachim Spoerhase
    • 4
  • Alexander Wolff
    • 4
  1. 1.Dept. of Comp. Sci.University of ArizonaTucsonU.S.A.
  2. 2.AT&T Labs ResearchFlorham ParkU.S.A.
  3. 3.Wilhelm-Schickard-Institut für InformatikUniversität TübingenGermany
  4. 4.Institut für InformatikUniversität WürzburgGermany

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