Approximation Algorithms for Submodular Multiway Partition
Chandra Chekuri, Alina Ene

TL;DR
This paper develops approximation algorithms for the Submodular Multiway Partition problem, improving previous bounds by leveraging a convex relaxation based on the Lovász extension for arbitrary submodular functions.
Contribution
It introduces a 2-approximation for general submodular functions and a better 1.5-approximation for symmetric functions, advancing the state-of-the-art in submodular partitioning.
Findings
Achieved a 2-approximation for SubMP with arbitrary submodular functions.
Improved the approximation ratio to 1.5-1/k for symmetric submodular functions.
Utilized a convex relaxation based on the Lovász extension to derive these algorithms.
Abstract
We study algorithms for the Submodular Multiway Partition problem (SubMP). An instance of SubMP consists of a finite ground set , a subset of elements called terminals, and a non-negative submodular set function on provided as a value oracle. The goal is to partition into sets such that for , and is minimized. SubMP generalizes some well-known problems such as the Multiway Cut problem in graphs and hypergraphs, and the Node-weighed Multiway Cut problem in graphs. SubMP for arbitrarysubmodular functions (instead of just symmetric functions) was considered by Zhao, Nagamochi and Ibaraki \cite{ZhaoNI05}. Previous algorithms were based on greedy splitting and divide and conquer strategies. In very recent work \cite{ChekuriE11} we proposed a…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Cryptography and Data Security
