Improved Steiner tree approximation in graphs
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
A constant factor approximation for the single sink edge installation problems
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Approximating the Single-Sink Link-Installation Problem in Network Design
SIAM Journal on Optimization
The Single-Sink Buy-at-Bulk LP Has Constant Integrality Gap
Proceedings of the 9th International IPCO Conference on Integer Programming and Combinatorial Optimization
Simpler and better approximation algorithms for network design
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
A tight bound on approximating arbitrary metrics by tree metrics
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
ACM Transactions on Algorithms (TALG)
Improved approximation for single-sink buy-at-bulk
ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
Steiner Tree Approximation via Iterative Randomized Rounding
Journal of the ACM (JACM)
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Consider a given undirected graph G=(V,E) with non-negative edge lengths, a root node r@?V, and a set D@?V of demands with d"v representing the units of flow that demand v@?D wishes to send to the root. We are also given K types of cables, each with a specified capacity and cost per unit length. The single-sink buy-at-bulk (SSBB) problem asks for a low-cost installation of cables along the edges of G, such that the demands can simultaneously send their flow to root r. The problem is studied with and without the restriction that the flow from a node must follow a single path to the root. We are allowed to install zero or more copies of a cable type on each edge. The SSBB problem is NP-hard. In this paper, we present a 153.6-approximation algorithm for the SSBB problem improving the previous best ratio of 216. For the case in which the flow is splittable, we improve the previous best ratio of 76.8 to @a"K, where @a"K is less than 67.94 for all K. In particular, @a"2