On the maximum cardinality search lower bound for treewidth:

Abstract: "The Maximum Cardinality Search algorithm visits the vertices of a graph in some order, such that at each step, an unvisited vertex that has the largest number of visited neighbors becomes visited. An MCS-ordering of a graph is an ordering of the vertices that can be generated by the...

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Bibliographische Detailangaben
Hauptverfasser: Bodlaender, Hans L. (VerfasserIn), Koster, Arie M. C. A. (VerfasserIn)
Format: Buch
Sprache:English
Veröffentlicht: Berlin Konrad-Zuse-Zentrum für Informationstechnik 2004
Schriftenreihe:ZIB 2004,45
Schlagworte:
Zusammenfassung:Abstract: "The Maximum Cardinality Search algorithm visits the vertices of a graph in some order, such that at each step, an unvisited vertex that has the largest number of visited neighbors becomes visited. An MCS-ordering of a graph is an ordering of the vertices that can be generated by the Maximum Cardinality Search algorithm. The visited degree of a vertex v in an MCS-ordering is the number of neighbors of v that are before v in the ordering. The visited degree of an MCS-ordering [psi] of G is the maximum visited degree over all vertices v in [psi]. The maximum visited degree over all MCS-orderings of graph G is called its maximum visited degree. Lucena [14] showed that the treewidth of a graph G is at least its maximum visited degree. We show that the maximum visited degree is of size O(log n) for planar graphs, and give examples of planar graphs G with maximum visited degree k with O(k!) vertices, for all k [element of] N. Given a graph G, it is NP-complete to determine if its maximum visited degree is at least k, for any fixed k [> or =] 7. Also, this problem does not have a polynomial time approximation algorithm with constant ratio, unless P = NP. Variants of the problem are also shown to be NP-complete. We also propose and experimentally analysed some heuristics for the problem. Several tiebreakers for the MCS algorithm are proposed and evaluated. We also give heuristics that give upper bounds on the value of the maximum visited degree of a graph, which appear to give results close to optimal on many graphs from real life applications."
Beschreibung:32 S. graph. Darst.

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