Approximation algorithms for the Bipartite Multicut problem
نویسندگان
چکیده
منابع مشابه
Cs 598csc: Approximation Algorithms 1 the Multicut Problem
In the Multicut problem, we are given a graph G = (V,E), a capacity function that assigns a capacity ce to each edge e, and a set of pairs (s1, t1), ..., (sk, tk). The Multicut problem asks for a minimum capacity set of edges F ⊆ E such that removing the edges in F disconnects si and ti, for all i. Note that the Multicut problem generalizes the Multiway Cut problem that we saw in the last two l...
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We introduce the Bipartite Multi-cut problem. This is a generalization of the st-Min-cut problem, is similar to the Multi-cut problem (except for more stringent requirements) and also turns out to be an immediate generalization of the Min UnCut problem. We prove that this problem is NP-hard and then present LP and SDP based approximation algorithms. While the LP algorithm is based on the Garg-V...
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Given a graph G = (V, E) with nonnegative costs defined on edges, a positive integer k, and a collection of q terminal sets D = {S1, S2, . . . , Sq}, where each Si is a subset of V (G), the Generalized k-Multicut problem asks to find a set of edges C ⊆ E(G) at the minimum cost such that its removal from G cuts at least k terminal sets in D. A terminal subset Si is cut by C if all terminals in S...
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Let G = (V; E) be an undirected graph with a capacity function u : E!< + and let S 1 ; S 2 ; : : : ; S k be k commodities, where each S i consists of a pair of nodes. A set X of nodes is called feasible if it contains no S i , and a cut (X; X) is called feasible if X is feasible. Several optimization problems on feasible cuts are shown to be NP-hard. A 2-approximation algorithm for the minimum-...
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ژورنال
عنوان ژورنال: Information Processing Letters
سال: 2010
ISSN: 0020-0190
DOI: 10.1016/j.ipl.2010.02.002