Algorithms for Unipolar and Generalized Split Graphs

TL;DR

This paper introduces recognition algorithms for unipolar and generalized split graphs, leveraging minimal triangulation, and provides efficient solutions for key optimization problems within these graph classes.

Contribution

It presents a recognition algorithm for unipolar graphs using minimal triangulation and extends it to recognize generalized split graphs efficiently.

Findings

Recognition algorithm for unipolar graphs with O(nm') time complexity

Algorithms for maximum independent set and minimum clique cover in O(n+m) time

NP-Complete proof for the perfect code problem in unipolar graphs

Abstract

A graph $G=(V,E)$ is a {\it unipolar graph} if there exits a partition $V=V_1 \cup V_2$ such that, $V_1$ is a clique and $V_2$ induces the disjoint union of cliques. The complement-closed class of {\it generalized split graphs} are those graphs $G$ such that either $G$ {\it or} the complement of $G$ is unipolar. Generalized split graphs are a large subclass of perfect graphs. In fact, it has been shown that almost all $C_5$-free (and hence, almost all perfect graphs) are generalized split graphs. In this paper we present a recognition algorithm for unipolar graphs that utilizes a minimal triangulation of the given graph, and produces a partition when one exists. Our algorithm has running time O($nm^\prime$), where $m^\prime$ is the number of edges in a minimal triangulation of the given graph. Generalized split graphs can recognized via this algorithm in O($nm' + n\OL{m}'$) = O($n^3$) time. We give algorithms on unipolar graphs for finding a maximum independent set and a minimum clique cover in O($n+m$) time and for finding a maximum clique and a minimum proper coloring in O($n^{2.5}/\log n$), when a unipolar partition is given. These algorithms yield algorithms for the four optimization problems on generalized split graphs that have the same worst-case time bound. We also prove that the perfect code problem is NP-Complete for unipolar graphs.