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Computing branchwidth via efficient triangulations and blocks

Authors: Fomin, Fedor V.; Mazoit, Frédéric; Todinca, Ioan;

Computing branchwidth via efficient triangulations and blocks

Abstract

Minimal triangulations and potential maximal cliques are the main ingredients for a number of polynomial time algorithms on different graph classes computing the treewidth of a graph. Potential maximal cliques are also the main engine of the fastest so far O(1.9601^n)-time exact treewidth algorithm. Based on the recent results of Mazoit, we define the structures that can be regarded as minimal triangulations and potential maximal cliques for branchwidth: efficient triangulations and blocks. We show how blocks can be used to construct an algorithm computing the branchwidth of a graph on n vertices in time (2+√3)^n · n^O(1).

Country
France
Keywords

algorithm, Distance in graphs, exponential time algorithm, Applied Mathematics, efficient triangulations, [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], graph, Graph, [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], Branchwidth, Graph algorithms (graph-theoretic aspects), Graph theory (including graph drawing) in computer science, Discrete Mathematics and Combinatorics, exponential algorithms, Exponential time algorithm, branchwidth

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Average
Average
Green
hybrid