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Asymmetric k-center is log* n-hard to approximate
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Annual ACM Symposium on Theory of Computing archive
Proceedings of the thirty-sixth annual ACM symposium on Theory of computing table of contents
Chicago, IL, USA
SESSION: Session 1A table of contents
Pages: 21 - 27  
Year of Publication: 2004
ISBN:1-58113-852-0
Authors
Julia Chuzhoy  Technion, Haifa, Israel
Sudipto Guha  University of Pennsylvania, Philadelphia, PA
Eran Halperi  UC Berkeley, Berkeley, CA
Sanjeev Khanna  University of Pennsylvania, Philadelphia, PA
Guy Kortsarz  Rutgers University, Camden, NJ
Joseph (Seffi) Nao  Technion, Haifa, Israel
Sponsors
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 29,   Citation Count: 6
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ABSTRACT

In the Asymmetric k-Center problem, the input is an integer k and a complete digraph over n points together with a distance function obeying the directed triangle inequality. The goal is to choose a set of k points to serve as centers and to assign all the points to the centers, so that the maximum distance of any point to its center is as small as possible. We show that the Asymmetric k-Center problem is hard to approximate up to a factor of log* n - Θ(1) unless NP ⊆ DTIME(nlog log n). Since an O(log* n)-approximation algorithm is known for this problem, this essentially resolves the approximability of this problem. This is the first natural problem whose approximability threshold does not polynomially relate to the known approximation classes. We also resolve the approximability threshold of the metric k-Center problem with costs.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Julia Chuzhoy: colleagues
Sudipto Guha: colleagues
Eran Halperi: colleagues
Sanjeev Khanna: colleagues
Guy Kortsarz: colleagues
Joseph (Seffi) Nao: colleagues