Abstract
Answering an open question published in Operations Research (54, 73–91, 2006) in the area of network design and logistic optimization, we present the first constant-factor approximation algorithms for the problem combining facility location and cable installation in which capacity constraints are imposed on both facilities and cables.
We study the problem of designing a minimum cost network to serve client demands by opening facilities for service provision and installing cables for service shipment. Both facilities and cables have capacity constraints and incur buy-at-bulk costs. This Max SNP-hard problem arises in diverse applications and is shown in this paper to admit a combinatorial 19.84-approximation algorithm of cubic running time. This is achieved by an integration of primal-dual schema, Lagrangian relaxation, demand clustering and bi-factor approximation. Our techniques extend to several variants of this problem, which include those with unsplitable demands or requiring network connectivity, and provide constant-factor approximate algorithms in strongly polynomial time.
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X. Chen is Visiting Fellow, University of Warwick.
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Chen, X., Chen, B. Approximation Algorithms for Soft-Capacitated Facility Location in Capacitated Network Design. Algorithmica 53, 263–297 (2009). https://doi.org/10.1007/s00453-007-9032-7
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DOI: https://doi.org/10.1007/s00453-007-9032-7