Approximation algorithms and hardness of the k-route cut problem

Julia Chuzhoy, Yury Makarychev, Aravindan Vijayaraghavan, Yuan Zhou

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


We study the k-route cut problem: given an undirected edge-weighted graph G = (V, E), a collection {(s1, t1), (s2, t2), ⋯, (sr, tr)} of source-sink pairs, and an integer connectivity requirement k, the goal is to find a minimum-weight subset E′ of edges to remove, such that the connectivity of every pair (si, ti) falls below k. Specifically, in the edge-connectivity version, EC-kRC, the requirement is that there are at most (k. 1) edge-disjoint paths connecting si to ti in G\ E′, while in the vertex-connectivity version, VC-kRC, the same requirement is for vertex-disjoint paths. Prior to our work, poly-logarithmic approximation algorithms have been known for the special case where k ≤ 3, but no non-trivial approximation algorithms were known for any value k > 3, except in the single-source setting. We show an O(klog3/2 r)-approximation algorithm for EC-kRC with uniform edge weights, and several polylogarithmic bi-criteria approximation algorithms for EC-kRC and VC-kRC, where the connectivity requirement k is violated by a constant factor. We complement these upper bounds by proving that VC-kRC is hard to approximate to within a factor of k for some fixed ∈ > 0. We then turn to study a simpler version of VC-kRC, where only one source-sink pair is present. We give a simple bi-criteria approximation algorithm for this case, and show evidence that even this restricted version of the problem may be hard to approximate. For example, we prove that the single source-sink pair version of VC-kRC has no constant-factor approximation, assuming Feige's Random κ-AND assumption.

Original languageEnglish (US)
Article number2
JournalACM Transactions on Algorithms
Issue number1
StatePublished - Dec 1 2015


  • Approximation algorithm
  • K-route cut problem

ASJC Scopus subject areas

  • Mathematics (miscellaneous)


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