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

Published: 01 Jan 2015, Last Modified: 25 Jan 2025CoRR 2015EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: In Directed Multiway Cut(Dir-MC) the input is an edge-weighted directed graph $G=(V,E)$ and a set of $k$ terminal nodes $\{s_1,s_2,\ldots,s_k\} \subseteq V$; the goal is to find a min-weight subset of edges whose removal ensures that there is no path from $s_i$ to $s_j$ for any $i \neq j$. In Node-weighted Multiway Cut(Node-MC) the input is a node-weighted undirected graph $G$ and a set of $k$ terminal nodes $\{s_1,s_2,\ldots,s_k\} \subseteq V$; the goal is to remove a min-weight subset of nodes to disconnect each pair of terminals. Dir-MC admits a $2$-approximation [Naor, Zosin '97] and Node-MC admits a $2(1-\frac{1}{k})$-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 $k=2$ and in particular prove that the integrality gap of the LP relaxation is $2$ even in directed planar graphs.
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