Abstract
We consider a fault tolerant version of the metric facility location problem in which every city, j, is required to be connected to r j facilities. We give the first non-trivial approximation algorithm for this problem, having an approximation guarantee of 3·Hk, where k is the maximum requirement and Hk is the k-th harmonic number. Our algorithm is along the lines of [2] for the generalized Steiner network problem. It runs in phases, and each phase, using a generalization of the primal-dual algorithm of [4] for the metric facility location problem, reduces the maximum residual requirement by 1.
Research supported by NSF Grant CCR-9820896.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
A. Agrawal, P. Klein, and R. Ravi.When trees collide: An approximation algorithm for the generalized Steiner problem on networks. SIAM J. on Computing, 24:440–456, 1995.
M. Goemans, A. Goldberg, S. Plotkin, D. Shmoys, E. Tardos, and D. Williamson. Improved approximation algorithms for network design problems. Proc. 5th ACMSIAM Symp. on Discrete Algorithms, 223–232, 1994.
M. X. Goemans, D. P. Williamson. A general approximation technique for constrained forest problems. SIAM Journal of Computing, 24:296–317, 1995.
K. Jain and V. V. Vazirani. Approximation algorithms for metric facility location and k-median problems using the primal-dual schema and Lagrangian relaxation. To appear in JACM.
D. P. Williamson, M. X. Goemans, M. Mihail, and V. V. Vazirani. A primal-dual approximation algorithm for generalized Steiner network problems. Combinatorica, 15:435–454, December1995.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kamal, J., Vazirani, V.V. (2000). An Approximation Algorithm for the Fault Tolerant Metric Facility Location Problem. In: Jansen, K., Khuller, S. (eds) Approximation Algorithms for Combinatorial Optimization. APPROX 2000. Lecture Notes in Computer Science, vol 1913. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44436-X_18
Download citation
DOI: https://doi.org/10.1007/3-540-44436-X_18
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67996-7
Online ISBN: 978-3-540-44436-7
eBook Packages: Springer Book Archive