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A Tree Structure For Dynamic Facility Location

Authors Gramoz Goranci, Monika Henzinger, Dariusz Leniowski

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Subject Classification

ACM Subject Classification
  • Theory of computation → Facility location and clustering
Keywords
  • facility location
  • dynamic algorithm
  • approximation
  • doubling dimension

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Abstract

We study the metric facility location problem with client insertions and deletions. This setting differs from the classic dynamic facility location problem, where the set of clients remains the same, but the metric space can change over time. We show a deterministic algorithm that maintains a constant factor approximation to the optimal solution in worst-case time O~(2^{O(kappa^2)}) per client insertion or deletion in metric spaces while answering queries about the cost in O(1) time, where kappa denotes the doubling dimension of the metric. For metric spaces with bounded doubling dimension, the update time is polylogarithmic in the parameters of the problem.

Cite As Get BibTex

Gramoz Goranci, Monika Henzinger, and Dariusz Leniowski. A Tree Structure For Dynamic Facility Location. In 26th Annual European Symposium on Algorithms (ESA 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 112, pp. 39:1-39:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/LIPIcs.ESA.2018.39

Author Details

Gramoz Goranci
  • University of Vienna, Faculty of Computer Science, Vienna, Austria
Monika Henzinger
  • University of Vienna, Faculty of Computer Science, Vienna, Austria
Dariusz Leniowski
  • University of Vienna, Faculty of Computer Science, Vienna, Austria

Funding

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 340506.

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