Computing the Exchange Number in Graphs with respect to Cycle Convexity

TL;DR

This paper investigates the computational complexity of the exchange number in graphs with respect to cycle convexity, providing NP-completeness results, characterizations, and polynomial algorithms for specific graph classes.

Contribution

It establishes NP-completeness for determining the exchange number, characterizes graphs with maximum exchange number, and offers polynomial algorithms for chordal and certain product graphs.

Findings

Deciding if $e_{cc}(G) \\geq k$ is NP-complete for $K_5$-free graphs.

Characterized all $n$-vertex graphs with exchange number $n-1$.

Derived formulas for exchange numbers of strong and lexicographic graph products.

Abstract

Given a graph $G$, a subset $S \subseteq V(G)$ is \textit{cycle convex}, if for any vertex $v \in V(G) \setminus S$, the induced subgraph, $G[S \cup \{v\}]$ cannot form a cycle containing the vertex $v$. The \textit{exchange number} of $G$, denoted by $e_{cc}(G)$ is the maximum cardinality of an $\textit{$E$-independent}$ set of $G$. This paper studies the computational complexity of determining the exchange number of graphs and provides exact values for some graph classes. Given a graph $G$ and a positive integer $k$, we show that deciding whether $e_{cc}(G) \geq k$ is NP-complete even if $G$ is a $K_5$-free graph. In contrast, we characterize all $n$-vertex graphs $G$ with exchange number $n-1$ and obtain closed formulas for chordal graphs $G$ whose blocks lie in a single chain, which leads to polynomial-time algorithms for computing $e_{cc}(G)$. We also establish a lower bound for the exchange number of the Cartesian product of general graphs and by using the results of Anand et al. \cite{bijo2}, we derive an explicit formula for the exchange number of strong and lexicographic graph products.