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The 43rd Annual IEEE Symposium on Foundations of Computer Science (FOCS'02)
A Constant-Factor Approximation Algorithm for the Multicommodity Rent-or-Buy Problem
Vancouver, BC, Canada
November 16-November 19
ISBN: 0-7695-1822-2
Amit Kumar, Cornell University
Anupam Gupta, Lucent Bell Labs
Tim Roughgarden, Cornell University

We present the first constant-factor approximation algorithm for network design with multiple commodities and economies of scale. We consider the rent-or-buy problem, a type of multicommodity buy-at-bulk network design in which there are two ways to install capacity on any given edge. Capacity can be rented, with cost incurred on a per-unit of capacity basis, or bought, which allows unlimited use after payment of a large fixed cost. Given a graph and a set of source-sink pairs, we seek a minimum-cost way of installing sufficient capacity on edges so that a prescribed amount of flow can be sent simultaneously from each source to the corresponding sink.

Recent work on buy-at-bulk network design has concentrated on the special case where all sinks are identical; existing constant-factor approximation algorithms for this special case make crucial use of the assumption that all commodities ship flow to the same sink vertex and do not obviously extend to the multicommodity rent-or-buy problem. Prior to our work, the best heuristics for the multicommodity rent-or-buy problem achieved only logarithmic performance guarantees and relied on the machinery of relaxed metrical task systems or of metric embeddings. By contrast, we solve the network design problem directly via a novel primal-dual algorithm.

Citation:
Amit Kumar, Anupam Gupta, Tim Roughgarden, "A Constant-Factor Approximation Algorithm for the Multicommodity Rent-or-Buy Problem," focs, pp.333, The 43rd Annual IEEE Symposium on Foundations of Computer Science (FOCS'02), 2002
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