A randomized algorithm for online unit clustering

  • Authors:
  • Timothy M. Chan;Hamid Zarrabi-Zadeh

  • Affiliations:
  • School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada;School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada

  • Venue:
  • WAOA'06 Proceedings of the 4th international conference on Approximation and Online Algorithms
  • Year:
  • 2006

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Abstract

In this paper, we consider the online version of the following problem: partition a set of input points into subsets, each enclosable by a unit ball, so as to minimize the number of subsets used. In the one-dimensional case, we show that surprisingly the naïve upper bound of 2 on the competitive ratio can be beaten: we present a new randomized 15/8-competitive online algorithm. We also provide some lower bounds and an extension to higher dimensions.