Approximation Algorithms for Buy-at-Bulk Geometric Network Design

Improved Approximation Algorithms for the Single-Sink Buy-at-Bulk Network Design Problems

LP-Based Approximation Algorithms for Facility Location in Buy-at-Bulk Network Design

We study problems that integrate buy-at-bulk network design into the classical (connected) facility location problem. In such problems, we need to open facilities, build a routing network, and route every client demand to an open facility. Furthermore, capacities of the edges can be purchased in discrete units from K different cable types with costs that satisfy economies of scale. We extend th...

A Constant-Factor Approximation Algorithm for the Multicommodity Rent-or-Buy Problem

We present the first constant-factor approximation algorithm for network design with multiple commodities andeconomies 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 givenedge. Capacity can be rented, with cost incurred on a per-unit of capacity basis, or bought, which allows u...

Approximation Algorithms for Network Design Problems with Node Weights

We consider several fundamental network design problems in undirected graphs with weights (costs) on both edges and nodes. We obtain the first poly-logarithmic approximation ratios for some classical problems that have been studied in the edge-weighted setting. Our main results are the following. • An O(log n) approximation for the Steiner forest problem. • An O(log n) approximation for the sin...

Cost-Distance: Two Metric Network Design

We present the COST-DISTANCE problem: finding a Steiner tree which optimizes the sum of edge costs along one metric and the sum of source-sink distances along an unrelated second metric. We give the first known randomized approximation scheme for COST-DISTANCE, where is the number of sources. We reduce several common network design problems to COST-DISTANCE, obtaining (in some cases) the first ...