A characterization of interval nest digraphs

📅 2026-03-09
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This work addresses the important subclass of interval nest digraphs by introducing the notion of a “nested ordering.” It provides the first complete characterization of this graph class through a linear vertex ordering that forbids specific patterns, thereby establishing an equivalence between interval nest digraphs and such orderings. By integrating tools from graph theory, combinatorial structure analysis, and interval representation models, the study achieves a full structural characterization of interval nest digraphs. This result fills a notable gap in the theory of forbidden patterns for vertex orderings among major subclasses of interval digraphs, offering a foundational insight into their combinatorial properties.

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📝 Abstract
A digraph consisting of a set of vertices $V$ and a set of arcs $E$ is called an interval digraph if there exists a family of closed intervals $\{I_u,J_u\}_{u \in V}$ such that $uv$ is an arc if and only if the intersection of $I_u$ and $J_v$ is non-empty. Interval digraphs naturally generalize interval graphs, by extending the classical interval intersection model to directed graphs. Several subclasses of interval digraphs have been studied in the literature-such as balanced, chronological and catch interval digraphs-each characterized by admitting interval representations that satisfy specific restrictions. Among these, interval nest digraphs are the ones that admit an interval representation in which $J_u$ is contained in $I_u$ for all vertices $u$ of $V$. In this work, we provide a complete characterization of interval nest digraphs in terms of vertex linear orderings with forbidden patterns, which we call nest orderings. This result completes the picture of vertex-ordering characterizations among the main subclasses of interval digraphs.
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interval nest digraphs
vertex ordering
forbidden patterns
characterization
interval digraphs
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interval nest digraphs
vertex ordering
forbidden patterns
nest orderings
interval digraph characterization
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Ayelén Alcantar
Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Matemática, Buenos Aires, Argentina; CONICET-Universidad de Buenos Aires, Instituto de Cálculo (IC), Buenos Aires, Argentina
F
Flavia Bonomo
Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Computación, Buenos Aires, Argentina; CONICET-Universidad de Buenos Aires, Instituto de Investigación en Ciencias de la Computación (ICC), Buenos Aires, Argentina
G
Guillermo Durán
Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Matemática, Buenos Aires, Argentina; CONICET-Universidad de Buenos Aires, Instituto de Cálculo (IC), Buenos Aires, Argentina; Universidad de Chile, Facultad de Ciencias Físicas y Matemáticas, Departamento de Ingeniería Industrial, Santiago, Chile
Nina Pardal
Nina Pardal
Lecturer, University of Huddersfield - ICC, Universidad de Buenos Aires
logicreasoningknowledge representationgraph theorydatabases