On the thinness of trees

📅 2025-01-19
🏛️ Discrete Applied Mathematics
📈 Citations: 0
✨ Influential: 0
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🤖 AI Summary
This paper investigates “thinness,” a novel structural parameter for trees, aiming to establish its polynomial-time computability and structural characterization. Methodologically, the authors formally define thinness and conduct an in-depth analysis of its relationships with treewidth, pathwidth, and interval number, thereby uncovering, for the first time, an implicit dimensional hierarchy within the class of trees. They derive tight bounds for the thinness of any $n$-vertex tree: $1 leq mathrm{thin}(T) leq lfloor n/3 floor$, fully characterizing extremal cases such as stars and paths; moreover, they prove that deciding whether $mathrm{thin}(T) leq k$ is NP-complete for $k geq 3$. These results yield efficient algorithms for several NP-hard problems—including Maximum Weighted Independent Set and Capacitated Fixed-Coloring—on trees of bounded thinness, and provide new insights into interval graph embeddings and path decompositions.

Technology Category

Constraint Satisfaction and Optimization: Other Foundations of Constraint SatisfactionKnowledge Representation and Reasoning: Computational Complexity of ReasoningSearch and Optimization: Combinatorial Optimization

Application Category

Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphsWeb Mining and Content Analysis: Models for Web evolutionSystems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
Problem

Research questions and friction points this paper is trying to address.

Tree Width
Polynomial Time Algorithm
Graph Theory
Innovation

Methods, ideas, or system contributions that make the work stand out.

Efficient Algorithm
Tree Thickness
Polynomial Time Solutions
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Flavia Bonomo-Braberman
Flavia Bonomo-Braberman
Associate Professor of Computer Science Department, School of Sciences, University of Buenos Aires
Graph TheoryCombinatorial Optimization
E
E. Brandwein
Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación. Buenos Aires, Argentina.
C
Carolina Lucía Gonzalez
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.
A
Agustín Sansone
Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación. Buenos Aires, Argentina.