e-approximations with minimum packing constraint violation (extended abstract)
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
A General Approximation Technique for Constrained Forest Problems
SIAM Journal on Computing
Approximation algorithms for facility location problems (extended abstract)
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Provisioning a virtual private network: a network design problem for multicommodity flow
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Primal-Dual Algorithms for Connected Facility Location Problems
APPROX '02 Proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization
Simpler and better approximation algorithms for network design
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Building Steiner trees with incomplete global knowledge
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Improved Primal-Dual Approximation Algorithm for the Connected Facility Location Problem
COCOA 2008 Proceedings of the 2nd international conference on Combinatorial Optimization and Applications
Concurrency and Computation: Practice & Experience
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We study the Connected Facility Location problems. We are given a connected graph G = (V,E) with non-negative edge cost ce for each edge e ∈ E, a set of clients D ⊆ V such that each client j ∈ D has positive demand dj and a set of facilities F ⊆ V each has non-negative opening cost fi and capacity to serve all client demands. The objective is to open a subset of facilities, say F, to assign each client j ∈ D to exactly one open facility i(j) and to connect all open facilities by a Steiner tree T such that the cost Σi∈F fi + Σj∈D djCi(j)j + M Σe∈T Ce is minimized. We propose a LP-rounding based 8.29 approximation algorithm which improves the previous bound 8.55. We also consider the problem when opening cost of all facilities are equal. In this case we give a 7.0 approximation algorithm.