Approximation and hardness results for label cut and related problems

Peng Zhang (), Jin-Yi Cai (), Lin-Qing Tang () and Wen-Bo Zhao ()
Additional contact information
Peng Zhang: Shandong University
Jin-Yi Cai: University of Wisconsin
Lin-Qing Tang: Chinese Academy of Sciences
Wen-Bo Zhao: University of California

Journal of Combinatorial Optimization, 2011, vol. 21, issue 2, No 3, 192-208

Abstract: Abstract We investigate a natural combinatorial optimization problem called the Label Cut problem. Given an input graph G with a source s and a sink t, the edges of G are classified into different categories, represented by a set of labels. The labels may also have weights. We want to pick a subset of labels of minimum cardinality (or minimum total weight), such that the removal of all edges with these labels disconnects s and t. We give the first non-trivial approximation and hardness results for the Label Cut problem. Firstly, we present an $O(\sqrt{m})$ -approximation algorithm for the Label Cut problem, where m is the number of edges in the input graph. Secondly, we show that it is NP-hard to approximate Label Cut within $2^{\log ^{1-1/\log\log^{c}n}n}$ for any constant c

Keywords: Label cut; Approximation algorithms; Approximation hardness; Combinatorial optimization (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10878-009-9222-0

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