Algorithms and Complexity of Hedge Cluster Deletion Problems

Abstract: A hedge graph is a graph whose edge set has been partitioned into groups called hedges. Here we consider a generalization of the well-known \textsc{Cluster Deletion} problem, named \textsc{Hedge Cluster Deletion}. The task is to compute the minimum number of hedges of a hedge graph so that their removal results in a graph that is isomorphic to a disjoint union of cliques. We show that for graphs that contain bounded size of vertex-disjoint 3-vertex-paths as subgraphs, \textsc{Hedge Cluster Deletion} can be solved in polynomial time. Regarding its approximability, we prove that the problem is tightly connected to the related complexity of the \textsc{Min Horn Deletion} problem, a well-known boolean CSP problem. Our connection shows that it is NP-hard to approximate \textsc{Hedge Cluster Deletion} within factor $2^{O(\log^{1-ε} r)}$ for any $ε>0$, where $r$ is the number of hedges in a given hedge graph. Based on its classified (in)approximability and the difficulty imposed by the structure of almost all non-trivial graphs, we consider the hedge underlying structure. We give a polynomial-time algorithm with constant approximation ratio for \textsc{Hedge Cluster Deletion} whenever each triangle of the input graph is covered by at most two hedges. On the way to this result, an interesting ingredient that we solved efficiently is a variant of the \textsc{Vertex Cover} problem in which apart from the desired vertex set that covers the edge set, a given set of vertex-constraints should also be included in the solution. Moreover, as a possible workaround for the existence of efficient exact algorithms, we propose the hedge intersection graph which is the intersection graph spanned by the hedges. Towards this direction, we give a polynomial-time algorithm for \textsc{Hedge Cluster Deletion} whenever the hedge intersection graph is acyclic.