Augmenting graphs to meet edge-connectivity requirements
SIAM Journal on Discrete Mathematics
Approximation algorithms for graph augmentation
Journal of Algorithms
A General Approximation Technique for Constrained Forest Problems
SIAM Journal on Computing
Approximation algorithms for finding highly connected subgraphs
Approximation algorithms for NP-hard problems
Discrete Applied Mathematics - Special issue: Special issue devoted to the fifth annual international computing and combinatories conference (COCOON'99) Tokyo, Japan 26-28 July 1999
On 2-Coverings and 2-Packings of Laminar Families
ESA '99 Proceedings of the 7th Annual European Symposium on Algorithms
A Factor 2 Approximation Algorithm for the Generalized Steiner Network Problem
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
A unified approach to approximating partial covering problems
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Path hitting in acyclic graphs
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
A 1.5-approximation algorithm for augmenting edge-connectivity of a graph from 1 to 2
Information Processing Letters
Augmenting the edge-connectivity of a spider tree
ISAAC'04 Proceedings of the 15th international conference on Algorithms and Computation
Edge-Connectivity augmentation and network matrices
WG'04 Proceedings of the 30th international conference on Graph-Theoretic Concepts in Computer Science
Kernelization and complexity results for connectivity augmentation problems
WADS'07 Proceedings of the 10th international conference on Algorithms and Data Structures
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We consider the following problem: given a connected graph G = (V, ƐE) and an additional edge set E, find a minimum size subset of edges F ⊆ E suchth at (V, Ɛ ∪ F) is 2-edge connected. This problem is NP-hard. For a long time, 2 was the best approximation ratio known. Recently, Nagamochi reported a (1.875 + Ɛ)-approximation algorithm. We give a new algorithm with a better approximation ratio of 3/2 and a practical running time.