2010•Unpublished venueOpen access

Fault-Tolerant Facility Location: a randomized dependent LP-rounding algorithm

Jarosław Byrka, Aravind Srinivasan, Chaitanya Swamy

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Abstract

Abstract We give a new randomized LP-rounding 1.725-approximation algorithm for the metric Fault- Tolerant Uncapacitated Facility Location problem. This improves on the previously best known 2.076-approximation algorithmof Swamy & Shmoys. To the best of our knowledge, our work provides the first application of a dependent-rounding technique in the domain of facility location. The analysis of our algorithm benefits from, and extends, methods developed for Uncapacitated Facility Location; it also helps uncover new properties of the dependent-rounding approach. An important concept that we develop is a novel, hierarchical clustering scheme. Typically, LP-rounding approximation algorithms for facility location problems are based on partitioning facilities into disjoint clusters and opening at least one facility in each cluster. We extend this approach and construct a laminar family of clusters, which then guides the rounding procedure. It allows to exploit properties of dependent rounding, and provides a quite tight analysis resulting in the improved approximation ratio.

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Abstract We give a new randomized LP-rounding 1.725-approximation algorithm for the metric Fault- Tolerant Uncapacitated Facility Location problem. This improves on the previously best known 2.076-approximation algorithmof Swamy & Shmoys. To the best of our knowledge, our work provides the first application of a dependent-rounding technique in the domain of facility location. The analysis of our algorithm benefits from, and extends, methods developed for Uncapacitated Facility Location; it also helps uncover new properties of the dependent-rounding approach. An important concept that we develop is a novel, hierarchical clustering scheme. Typically, LP-rounding approximation algorithms for facility location problems are based on partitioning facilities into disjoint clusters and opening at least one facility in each cluster. We extend this approach and construct a laminar family of clusters, which then guides the rounding procedure. It allows to exploit properties of dependent rounding, and provides a quite tight analysis resulting in the improved approximation ratio.

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Available abstract

Abstract We give a new randomized LP-rounding 1.725-approximation algorithm for the metric Fault- Tolerant Uncapacitated Facility Location problem. This improves on the previously best known 2.076-approximation algorithmof Swamy & Shmoys. To the best of our knowledge, our work provides the first application of a dependent-rounding technique in the domain of facility location. The analysis of our algorithm benefits from, and extends, methods developed for Uncapacitated Facility Location; it also helps uncover new properties of the dependent-rounding approach. An important concept that we develop is a novel, hierarchical clustering scheme. Typically, LP-rounding approximation algorithms for facility location problems are based on partitioning facilities into disjoint clusters and opening at least one facility in each cluster. We extend this approach and construct a laminar family of clusters, which then guides the rounding procedure. It allows to exploit properties of dependent rounding, and provides a quite tight analysis resulting in the improved approximation ratio.

Key concepts: Rounding, Randomized rounding, Computer science, Facility location problem, Metric (unit), Algorithm, Approximation algorithm, Domain (mathematical analysis)

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