English

$\ell_p$-norm Multiway Cut

Data Structures and Algorithms 2021-06-29 v1

Abstract

We introduce and study p\ell_p-norm-multiway-cut: the input here is an undirected graph with non-negative edge weights along with kk terminals and the goal is to find a partition of the vertex set into kk parts each containing exactly one terminal so as to minimize the p\ell_p-norm of the cut values of the parts. This is a unified generalization of min-sum multiway cut (when p=1p=1) and min-max multiway cut (when p=p=\infty), both of which are well-studied classic problems in the graph partitioning literature. We show that p\ell_p-norm-multiway-cut is NP-hard for constant number of terminals and is NP-hard in planar graphs. On the algorithmic side, we design an O(log2n)O(\log^2 n)-approximation for all p1p\ge 1. We also show an integrality gap of Ω(k11/p)\Omega(k^{1-1/p}) for a natural convex program and an O(k11/pϵ)O(k^{1-1/p-\epsilon})-inapproximability for any constant ϵ>0\epsilon>0 assuming the small set expansion hypothesis.

Keywords

Cite

@article{arxiv.2106.14840,
  title  = {$\ell_p$-norm Multiway Cut},
  author = {Karthekeyan Chandrasekaran and Weihang Wang},
  journal= {arXiv preprint arXiv:2106.14840},
  year   = {2021}
}
R2 v1 2026-06-24T03:41:00.068Z