Approximating the Weighted Minimum Label $s$-$t$ Cut Problem

TL;DR

This paper presents an approximation algorithm for the weighted Label s-t Cut problem, achieving an O(n^{2/3}) ratio, which was previously unknown for weighted cases, by interpreting label weights as length and capacity.

Contribution

The paper introduces a novel approximation algorithm for the weighted Label s-t Cut problem with ratio O(n^{2/3}), extending prior unweighted results.

Findings

Achieved an O(n^{2/3}) approximation ratio for the weighted Label s-t Cut problem.

Developed a mechanism interpreting label weights as both length and capacity.

Extended approximation techniques from unweighted to weighted label cut problems.

Abstract

In the weighted (minimum) {\sf Label $s$-$t$ Cut} problem, we are given a (directed or undirected) graph $G=(V,E)$, a label set $L = \{\ell_1, \ell_2, \dots, \ell_q \}$ with positive label weights $\{w_\ell\}$, a source $s \in V$ and a sink $t \in V$. Each edge edge $e$ of $G$ has a label $\ell(e)$ from $L$. Different edges may have the same label. The problem asks to find a minimum weight label subset $L'$ such that the removal of all edges with labels in $L'$ disconnects $s$ and $t$. The unweighted {\sf Label $s$-$t$ Cut} problem (i.e., every label has a unit weight) can be approximated within $O(n^{2/3})$, where $n$ is the number of vertices of graph $G$. However, it is unknown for a long time how to approximate the weighted {\sf Label $s$-$t$ Cut} problem within $o(n)$. In this paper, we provide an approximation algorithm for the weighted {\sf Label $s$-$t$ Cut} problem with ratio $O(n^{2/3})$. The key point of the algorithm is a mechanism to interpret label weight on an edge as both its length and capacity.