2 research outputs found

    Simple and Fast Rounding Algorithms for Directed and Node-weighted Multiway Cut

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    In Directed Multiway Cut(Dir-MC) the input is an edge-weighted directed graph G=(V,E)G=(V,E) and a set of kk terminal nodes {s1,s2,…,sk}βŠ†V\{s_1,s_2,\ldots,s_k\} \subseteq V; the goal is to find a min-weight subset of edges whose removal ensures that there is no path from sis_i to sjs_j for any iβ‰ ji \neq j. In Node-weighted Multiway Cut(Node-MC) the input is a node-weighted undirected graph GG and a set of kk terminal nodes {s1,s2,…,sk}βŠ†V\{s_1,s_2,\ldots,s_k\} \subseteq V; the goal is to remove a min-weight subset of nodes to disconnect each pair of terminals. Dir-MC admits a 22-approximation [Naor, Zosin '97] and Node-MC admits a 2(1βˆ’1k)2(1-\frac{1}{k})-approximation [Garg, Vazirani, Yannakakis '94], both via rounding of LP relaxations. Previous rounding algorithms for these problems, from nearly twenty years ago, are based on careful rounding of an "optimum" solution to an LP relaxation. This is particularly true for Dir-MC for which the rounding relies on a custom LP formulation instead of the natural distance based LP relaxation [Naor, Zosin '97]. In this paper we describe extremely simple and near linear-time rounding algorithms for Dir-MC and Node-MC via a natural distance based LP relaxation. The dual of this relaxation is a special case of the maximum multicommodity flow problem. Our algorithms achieve the same bounds as before but have the significant advantage in that they can work with "any feasible" solution to the relaxation. Consequently, in addition to obtaining "book" proofs of LP rounding for these two basic problems, we also obtain significantly faster approximation algorithms by taking advantage of known algorithms for computing near-optimal solutions for maximum multicommodity flow problems. We also investigate lower bounds for Dir-MC when k=2k=2 and in particular prove that the integrality gap of the LP relaxation is 22 even in directed planar graphs

    Approximating Multicut and the Demand Graph

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    In the minimum Multicut problem, the input is an edge-weighted supply graph G=(V,E)G=(V,E) and a simple demand graph H=(V,F)H=(V,F). Either GG and HH are directed (DMulC) or both are undirected (UMulC). The goal is to remove a minimum weight set of edges in GG such that there is no path from ss to tt in the remaining graph for any (s,t)∈F(s,t) \in F. UMulC admits an O(log⁑k)O(\log k)-approximation where kk is the vertex cover size of HH while the best known approximation for DMulC is min⁑{k,O~(n11/23)}\min\{k, \tilde{O}(n^{11/23})\}. These approximations are obtained by proving corresponding results on the multicommodity flow-cut gap. In contrast to these results some special cases of Multicut, such as the well-studied Multiway Cut problem, admit a constant factor approximation in both undirected and directed graphs. Motivated by both concrete instances from applications and abstract considerations, we consider the role that the structure of the demand graph HH plays in determining the approximability of Multicut. In undirected graphs our main result is a 22-approximation in nO(t)n^{O(t)} time when the demand graph HH excludes an induced matching of size tt. This gives a constant factor approximation for a specific demand graph that motivated this work. In contrast to undirected graphs, we prove that in directed graphs such approximation algorithms can not exist. Assuming the Unique Games Conjecture (UGC), for a large class of fixed demand graphs DMulC cannot be approximated to a factor better than worst-case flow-cut gap. As a consequence we prove that for any fixed kk, assuming UGC, DMulC with kk demand pairs is hard to approximate to within a factor better than kk. On the positive side, we prove an approximation of kk when the demand graph excludes certain graphs as an induced subgraph. This generalizes the Multiway Cut result to a much larger class of demand graphs
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