ISCAS OpenIR  > 基础软件与系统重点实验室
approximation and hardness results for label cut and related problems
Zhang Peng; Cai Jin-Yi; Tang Linqing; Zhao Wenbo
2009
Conference Name6th Annual Conference on Theory and Applications of Models of Computation, TAMC 2009
SourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages460-469
Conference Date43969
Conference PlaceChangsha, China
Publish PlaceGermany
ISSN3029743
ISBN9783642020162
Department(1) School of Computer Science and Technology, Shandong University, Jinan 250101, China; (2) Computer Sciences Department, University of Wisconsin, Madison, WI 53706, United States; (3) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100080, China; (4) Dept. of Computer Science and Engineering, University of California, San Diego, San Diego, CA 92093, United States
English AbstractWe 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(√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 2log1-1/log logc nn for any constant c < 1/2, where n is the input length of the problem. Thirdly, our techniques can be applied to other previously considered optimization problems. In particular we show that the Minimum Label Path problem has the same approximation hardness as that of Label Cut, simultaneously improving and unifying two known hardness results for this problem which were previously the best (but incomparable due to different complexity assumptions). © Springer-Verlag Berlin Heidelberg 2009.
KeywordApproximation Algorithms Combinatorial Optimization Computational Complexity Graph Theory Hardness
SponsorshipSouth Central University
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8462
Collection基础软件与系统重点实验室
Recommended Citation
GB/T 7714
Zhang Peng,Cai Jin-Yi,Tang Linqing,et al. approximation and hardness results for label cut and related problems[C]. Germany,2009:460-469.
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