Approximation and parameterized algorithms to find balanced connected partitions of graphs

Abstract: Partitioning a connected graph into $k$~vertex-disjoint connected subgraphs of similar (or given) orders is a classical problem that has been intensively investigated since late seventies. Given a connected graph $G=(V,E)$ and a weight function $w : V \to \mathbb{Q}<em>\geq$, a connected $k$-partition of $G$ is a partition of $V$ such that each class induces a connected subgraph. The balanced connected $k$-partition problem consists in finding a connected $k$-partition in which every class has roughly the same weight. To model this concept of balance, one may seek connected $k$-partitions that either maximize the weight of a lightest class $(\text{max-min BCP}_k)$ or minimize the weight of a heaviest class $(\text{min-max BCP}_k)$. Such problems are equivalent when $k=2$, but they are different when $k\geq 3$. In this work, we propose a simple pseudo-polynomial $\frac{k}{2}$-approximation algorithm for $\text{min-max BCP}_k$ which runs in time $\mathcal{O}(W|V||E|)$, where $W = \sum</em>{v \in V} w(v)$. Based on this algorithm and using a scaling technique, we design a (polynomial) $(\frac{k}{2} +\varepsilon)$-approximation for the same problem with running-time $\mathcal{O}(|V|<sup>3|E|/\varepsilon)$, for any fixed $\varepsilon&gt;0$. Additionally, we propose a fixed-parameter tractable algorithm based on integer linear programming for the unweighted $\text{max-min BCP}_k$ parameterized by the size of a vertex cover.