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ABSTRACT

We study the multicommodity buy-at-bulk network design problem in which we seek to design a network that satisfies the demands between terminals from a given set of source-sink pairs. The key characteristic of this problem is the fact that the cost functions associated with the edges of the graph are sub-additive monotone and hence experience economies of scale. In the non-uniform case, each edge has its own cost function -- possibly different from other edges. Special cases of this problem have been studied extensively: there are approximation algorithms when the edge cost functions are identical or when all source-sink pairs share the same source. We present the first non-trivial approximation algorithm for the general case. Our algorithm is an extremely simple randomized greedy algorithm and has an approximation guarantee of exp(O√ln n ln ln n)) when the instance has at most n source-sink pairs with unit demands. In the case of general demands, this yields an approximation factor of exp(O √ln N ln ln N)), where N is the sum of all demands.

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INDEX TERMS

Primary Classification:
  F. Theory of Computation
  F.2 ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY

General Terms:
Algorithms, Design, Theory

Keywords:
approximation algorithms, buy-at-bulk, multicommodity, network design, non-uniform