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Facility Location with Dynamic Distance Functions

Author

Listed:
  • Randeep Bhatia

    (Bell Labs)

  • Sudipto Guha

    (Stanford University)

  • Samir Khuller

    (University of Maryland)

  • Yoram J. Sussmann

    (University of Maryland)

Abstract

Facility location problems have always been studied with theassumption that the edge lengths in the network are static anddo not change over time. The underlying network could be used to model a city street networkfor emergency facility location/hospitals, or an electronic network for locating information centers. In any case, it is clear that due to trafficcongestion the traversal time on links changes with time. Very often, we have estimates as to how the edge lengths change over time, and our objective is to choose a set of locations (vertices) ascenters, such that at every time instant each vertex has a center close to it (clearly, the center close to a vertex may change over time). We also provide approximation algorithms as well as hardness results forthe K-center problem under this model. This is the first comprehensive study regarding approximation algorithmsfor facility location for good time-invariant solutions.

Suggested Citation

  • Randeep Bhatia & Sudipto Guha & Samir Khuller & Yoram J. Sussmann, 1998. "Facility Location with Dynamic Distance Functions," Journal of Combinatorial Optimization, Springer, vol. 2(3), pages 199-217, September.
  • Handle: RePEc:spr:jcomop:v:2:y:1998:i:3:d:10.1023_a:1009796525600
    DOI: 10.1023/A:1009796525600
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    References listed on IDEAS

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    1. Constantine Toregas & Ralph Swain & Charles ReVelle & Lawrence Bergman, 1971. "The Location of Emergency Service Facilities," Operations Research, INFORMS, vol. 19(6), pages 1363-1373, October.
    2. Daniel Serra & Vladimir Marianov, 1996. "The P-median problem in a changing network: The case of Barcelona," Economics Working Papers 180, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Arthur Warburton, 1987. "Approximation of Pareto Optima in Multiple-Objective, Shortest-Path Problems," Operations Research, INFORMS, vol. 35(1), pages 70-79, February.
    4. Refael Hassin, 1992. "Approximation Schemes for the Restricted Shortest Path Problem," Mathematics of Operations Research, INFORMS, vol. 17(1), pages 36-42, February.
    5. Dorit S. Hochbaum & David B. Shmoys, 1985. "A Best Possible Heuristic for the k -Center Problem," Mathematics of Operations Research, INFORMS, vol. 10(2), pages 180-184, May.
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    Cited by:

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    2. Mihelic, Jurij & Mahjoub, Amine & Rapine, Christophe & Robic, Borut, 2010. "Two-stage flexible-choice problems under uncertainty," European Journal of Operational Research, Elsevier, vol. 201(2), pages 399-403, March.

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