The problem of orienting the edges of an undirected graph such that the resulting digraph is acyclic and has a single source s and a single sink t has a long tradition in graph theory and is central to many graph drawing algorithms. Such an orientation is called an st-orientation. We address the problem of computing storientations of undirected graphs with the minimum number of transitive edges. We prove that the problem is NP-hard in the general case. For planar graphs we describe an ILP (Integer Linear Programming) model that is fast in practice, namely it takes on average less than 1 second for graphs with up to 100 vertices, and about 10 seconds for larger instances with up to 1000 vertices. We experimentally show that optimum solutions significantly reduce (35% on average) the number of transitive edges with respect to unconstrained st-orientations computed via classical st-numbering algorithms. Moreover, focusing on popular graph drawing algorithms that apply an st-orientation as a preliminary step, we show that reducing the number of transitive edges leads to drawings that are much more compact (with an improvement between 30% and 50% for most of the instances).
Binucci, C., Didimo, W., Patrignani, M. (2023). $st$-Orientations with Few Transitive Edges. JOURNAL OF GRAPH ALGORITHMS AND APPLICATIONS, 27(8), 625-650 [10.7155/jgaa.00638].
$st$-Orientations with Few Transitive Edges
Patrignani, Maurizio
2023-01-01
Abstract
The problem of orienting the edges of an undirected graph such that the resulting digraph is acyclic and has a single source s and a single sink t has a long tradition in graph theory and is central to many graph drawing algorithms. Such an orientation is called an st-orientation. We address the problem of computing storientations of undirected graphs with the minimum number of transitive edges. We prove that the problem is NP-hard in the general case. For planar graphs we describe an ILP (Integer Linear Programming) model that is fast in practice, namely it takes on average less than 1 second for graphs with up to 100 vertices, and about 10 seconds for larger instances with up to 1000 vertices. We experimentally show that optimum solutions significantly reduce (35% on average) the number of transitive edges with respect to unconstrained st-orientations computed via classical st-numbering algorithms. Moreover, focusing on popular graph drawing algorithms that apply an st-orientation as a preliminary step, we show that reducing the number of transitive edges leads to drawings that are much more compact (with an improvement between 30% and 50% for most of the instances).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.