| Simpler and better approximation algorithms for network design |
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Annual ACM Symposium on Theory of Computing
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Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
table of contents
San Diego, CA, USA
SESSION: Session 7B
table of contents
Pages: 365 - 372
Year of Publication: 2003
ISBN:1-58113-674-9
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Downloads (6 Weeks): 14, Downloads (12 Months): 107, Citation Count: 24
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ABSTRACT
We give simple and easy-to-analyze randomized approximation algorithms for several well-studied NP-hard network design problems. Our algorithms improve over the previously best known approximation ratios. Our main results are the following. - We give a randomized 3.55-approximation algorithm for the connected facility location problem. The algorithm requires three lines to state, one page to analyze, and improves the best-known performance guarantee for the problem.
- We give a 5.55-approximation algorithm for virtual private network design. Previously, constant-factor approximation algorithms were known only for special cases of this problem.
- We give a simple constant-factor approximation algorithm for the single-sink buy-at-bulk network design problem. Our performance guarantee improves over what was previously known, and is an order of magnitude improvement over previous combinatorial approximation algorithms for the problem.
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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Naveen Garg , Rohit Khandekar , Goran Konjevod , R. Ravi , F. S. Salman , Amitabh Sinha, On the Integrality Gap of a Natural Formulation of the Single-Sink Buy-at-Bulk Network Design Problem, Proceedings of the 8th International IPCO Conference on Integer Programming and Combinatorial Optimization, p.170-184, June 13-15, 2001
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Anupam Gupta , Jon Kleinberg , Amit Kumar , Rajeev Rastogi , Bulent Yener, Provisioning a virtual private network: a network design problem for multicommodity flow, Proceedings of the thirty-third annual ACM symposium on Theory of computing, p.389-398, July 2001, Hersonissos, Greece
[doi> 10.1145/380752.380830]
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CITED BY 24
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Anupam Gupta , Martin Pál , R. Ravi , Amitabh Sinha, Boosted sampling: approximation algorithms for stochastic optimization, Proceedings of the thirty-sixth annual ACM symposium on Theory of computing, June 13-16, 2004, Chicago, IL, USA
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Lisa Fleischer , Jochen Könemann , Stefano Leonardi , Guido Schäfer, Simple cost sharing schemes for multicommodity rent-or-buy and stochastic Steiner tree, Proceedings of the thirty-eighth annual ACM symposium on Theory of computing, May 21-23, 2006, Seattle, WA, USA
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Naveen Garg , Anupam Gupta , Stefano Leonardi , Piotr Sankowski, Stochastic analyses for online combinatorial optimization problems, Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms, p.942-951, January 20-22, 2008, San Francisco, California
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Friedrich Eisenbrand , Fabrizio Grandoni , Thomas Rothvoß , Guido Schäfer, Approximating connected facility location problems via random facility sampling and core detouring, Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms, p.1174-1183, January 20-22, 2008, San Francisco, California
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C. Chekuri , M. T. Hajiaghayi , G. Kortsarz , M. R. Salavatipour, Approximation algorithms for node-weighted buy-at-bulk network design, Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, p.1265-1274, January 07-09, 2007, New Orleans, Louisiana
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