English

Cluster Deletion on Interval Graphs and Split Related Graphs

Data Structures and Algorithms 2019-04-23 v1

Abstract

In the {\sc Cluster Deletion} problem the goal is to remove the minimum number of edges of a given graph, such that every connected component of the resulting graph constitutes a clique. It is known that the decision version of {\sc Cluster Deletion} is NP-complete on (P5P_5-free) chordal graphs, whereas {\sc Cluster Deletion} is solved in polynomial time on split graphs. However, the existence of a polynomial-time algorithm of {\sc Cluster Deletion} on interval graphs, a proper subclass of chordal graphs, remained a well-known open problem. Our main contribution is that we settle this problem in the affirmative, by providing a polynomial-time algorithm for {\sc Cluster Deletion} on interval graphs. Moreover, despite the simple formulation of the algorithm on split graphs, we show that {\sc Cluster Deletion} remains NP-complete on a natural and slight generalization of split graphs that constitutes a proper subclass of P5P_5-free chordal graphs. To complement our results, we provide two polynomial-time algorithms for {\sc Cluster Deletion} on subclasses of such generalizations of split graphs.

Keywords

Cite

@article{arxiv.1904.09470,
  title  = {Cluster Deletion on Interval Graphs and Split Related Graphs},
  author = {Athanasios L. Konstantinidis and Charis Papadopoulos},
  journal= {arXiv preprint arXiv:1904.09470},
  year   = {2019}
}
R2 v1 2026-06-23T08:45:23.226Z