Algorithmic Applications of Tree-Cut Width

TL;DR

This paper explores the algorithmic potential of the graph parameter tree-cut width, introducing new algorithms for certain problems and proving hardness results for others, thereby advancing understanding of its computational applications.

Contribution

It provides the first algorithmic applications of tree-cut width, including FPT algorithms for some problems and hardness results for others.

Findings

FPT algorithms for Capacitated Vertex Cover, Capacitated Dominating Set, and Imbalance.

W[1]-hardness results for List Coloring, Precoloring Extension, and Boolean CSP.

Introduction of nice tree-cut decompositions.

Abstract

The recently introduced graph parameter tree-cut width plays a similar role with respect to immersions as the graph parameter treewidth plays with respect to minors. In this paper, we provide the first algorithmic applications of tree-cut width to hard combinatorial problems. Tree-cut width is known to be lower-bounded by a function of treewidth, but it can be much larger and hence has the potential to facilitate the efficient solution of problems that are not known to be fixed-parameter tractable (FPT) when parameterized by treewidth. We introduce the notion of nice tree-cut decompositions and provide FPT algorithms for the showcase problems Capacitated Vertex Cover, Capacitated Dominating Set, and Imbalance parameterized by the tree-cut width of an input graph. On the other hand, we show that List Coloring, Precoloring Extension, and Boolean CSP (the latter parameterized by the tree-cut width of the incidence graph) are W[1]-hard and hence unlikely to be fixed-parameter tractable when parameterized by tree-cut width.