Approximation algorithms for maximally balanced connected graph partition

TL;DR

This paper develops approximation algorithms for the max-min balanced connected graph partition problem, providing improved bounds for specific cases and extending results to general k, with practical local improvement techniques.

Contribution

It introduces a new 3/2-approximation for 3-BGP and extends it to a k/2-approximation for general k-BGP, also improving the approximation for 4-BGP to 24/13.

Findings

A 3/2-approximation for 3-BGP.

A k/2-approximation for general k-BGP.

An improved 24/13-approximation for 4-BGP.

Abstract

Given a simple connected graph $G = (V, E)$, we seek to partition the vertex set $V$ into $k$ non-empty parts such that the subgraph induced by each part is connected, and the partition is maximally balanced in the way that the maximum cardinality of these $k$ parts is minimized. We refer this problem to as {\em min-max balanced connected graph partition} into $k$ parts and denote it as {\sc $k$-BGP}. The general vertex-weighted version of this problem on trees has been studied since about four decades ago, which admits a linear time exact algorithm; the vertex-weighted {\sc $2$-BGP} and {\sc $3$-BGP} admit a $5/4$-approximation and a $3/2$-approximation, respectively; but no approximability result exists for {\sc $k$-BGP} when $k \ge 4$, except a trivial $k$-approximation. In this paper, we present another $3/2$-approximation for our cardinality {\sc $3$-BGP} and then extend it to become a $k/2$-approximation for {\sc $k$-BGP}, for any constant $k \ge 3$. Furthermore, for {\sc $4$-BGP}, we propose an improved $24/13$-approximation. To these purposes, we have designed several local improvement operations, which could be useful for related graph partition problems.