An Improved Algorithm for Online Unit Clustering

  • Hamid Zarrabi-Zadeh
  • Timothy M. Chan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4598)


We revisit the online unit clustering problem in one dimension which we recently introduced at WAOA’06: given a sequence of n points on the line, the objective is to partition the points into a minimum number of subsets, each enclosable by a unit interval. We present a new randomized online algorithm that achieves expected competitive ratio 11/6 against oblivious adversaries, improving the previous ratio of 15/8. This immediately leads to improved upper bounds for the problem in two and higher dimensions as well.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hamid Zarrabi-Zadeh
    • 1
  • Timothy M. Chan
    • 1
  1. 1.School of Computer Science, University of Waterloo, Waterloo, Ontario, N2L 3G1Canada

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