| Sharing the cost more efficiently: improved approximation for multicommodity rent-or-buy |
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Symposium on Discrete Algorithms
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Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
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Vancouver, British Columbia
SESSION: Session 4C
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Pages: 375 - 384
Year of Publication: 2005
ISBN:0-89871-585-7
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Society for Industrial and Applied Mathematics
Philadelphia, PA, USA
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Downloads (6 Weeks): 6, Downloads (12 Months): 19, Citation Count: 5
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ABSTRACT
In the multicommodity rent-or-buy (MROB) network design problem we are given a network together with a set of k terminal pairs (s1, t1),.....,(sk, tk). The goal is to provision the network so that a given amount of low can be shipped between si and ti for all 1 ≤ i ≤ k simultaneously. In order to provision the network one can either rent capacity on edges at some cost per unit of ow, or buy them at some larger fixed cost. Bought edges have no incremental, ow-dependent cost. The overall objective is to minimize the total provisioning cost.Recently, Gupta et al. [8] presented a 12 approximation for the MROB problem. Their algorithm chooses a subset of the terminal pairs in the graph at random and then buys the edges of an approximate Steiner forest for these pairs. This technique has previously been introduced [9] for the single sink rent-or-buy network design problem.In this paper we give a 6.828-approximation for the MROB problem by refining the algorithm of Gupta et al. and simplifying their analysis. The improvement in our paper is based on a more careful adaptation and simplified analysis of the primal-dual algorithm for the Steiner forest problem due to Agrawal, Klein and Ravi [1]. Our result significantly reduces the gap between the single-sink [9] and multi-sink case.
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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L. Becchetti, J. Könemann, S. Leonardi, and M. Pál. Sharing the cost more efficiently: Improved approximation for multicommodity rent-or-buy. See www.math.uwaterloo.ca/~jochen/docs/mrob-jv.pdf, 2004.
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J. Könemann. Approximation Algorithms for Minimum-Cost Low-Degree Subgraphs. PhD thesis, Carnegie Mellon University, 2003.
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J. Könemann and R. Ravi. Quasi-polynomial time approximation algorithm for low-degree minimum-cost steiner trees. In Proceedings of Foundations of Software Technology and Theoretical Computer Science., 2003.
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CITED BY 5
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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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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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