Algorithms for Generating Convex Sets in Acyclic Digraphs

TL;DR

This paper introduces efficient algorithms for enumerating all convex and connected convex sets in acyclic digraphs, outperforming previous methods and applicable to related undirected graphs.

Contribution

The authors develop optimal algorithms for enumerating convex and connected convex sets in acyclic digraphs with improved time complexity.

Findings

Algorithms outperform existing methods in computational experiments.

Time complexity is linear in the number of convex sets.

Applicable to connected sets in undirected graphs with improved efficiency.

Abstract

A set $X$ of vertices of an acyclic digraph $D$ is convex if $X\neq \emptyset$ and there is no directed path between vertices of $X$ which contains a vertex not in $X$. A set $X$ is connected if $X\neq \emptyset$ and the underlying undirected graph of the subgraph of $D$ induced by $X$ is connected. Connected convex sets and convex sets of acyclic digraphs are of interest in the area of modern embedded processor technology. We construct an algorithm $\cal A$ for enumeration of all connected convex sets of an acyclic digraph $D$ of order $n$. The time complexity of $\cal A$ is $O(n\cdot cc(D))$, where $cc(D)$ is the number of connected convex sets in $D$. We also give an optimal algorithm for enumeration of all (not just connected) convex sets of an acyclic digraph $D$ of order $n$. In computational experiments we demonstrate that our algorithms outperform the best algorithms in the literature. Using the same approach as for $\cal A$, we design an algorithm for generating all connected sets of a connected undirected graph $G$. The complexity of the algorithm is $O(n\cdot c(G)),$ where $n$ is the order of $G$ and $c(G)$ is the number of connected sets of $G.$ The previously reported algorithm for connected set enumeration is of running time $O(mn\cdot c(G))$, where $m$ is the number of edges in $G.$