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A Bicriteria Approximation Algorithm for the k-Center and k-Median Problems

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Approximation and Online Algorithms (WAOA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10787))

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Abstract

The k-center and k-median problems are two central clustering techniques that are well-studied and widely used. In this paper, we focus on possible simultaneous generalizations of these two problems and present a bicriteria approximation algorithm for them with constant approximation factor in both dimensions. We also extend our results to the so-called incremental setting, where cluster centers are chosen one by one and the resulting solution must have the property that the first k cluster centers selected must simultaneously be near-optimal for all values of k.

S. Alamdari and D. Shmoys—Supported in part by NSF CCF-1526067, CMMI-1537394, and CCF-1522054.

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Authors and Affiliations

  1. Cornell University, New York, NY, 14853, USA

    Soroush Alamdari & David Shmoys

Authors
  1. Soroush Alamdari
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  2. David Shmoys
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Corresponding author

Correspondence to Soroush Alamdari .

Editor information

Editors and Affiliations

  1. The University of Western Ontario, London, Ontario, Canada

    Roberto Solis-Oba

  2. German University of Technology in Oman, Muscat, Oman

    Rudolf Fleischer

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Alamdari, S., Shmoys, D. (2018). A Bicriteria Approximation Algorithm for the k-Center and k-Median Problems. In: Solis-Oba, R., Fleischer, R. (eds) Approximation and Online Algorithms. WAOA 2017. Lecture Notes in Computer Science(), vol 10787. Springer, Cham. https://doi.org/10.1007/978-3-319-89441-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-89441-6_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-89440-9

  • Online ISBN: 978-3-319-89441-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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