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Heuristic and metaheuristic methodsfor computing graph treewidth

Published online by Cambridge University Press:  15 April 2004

François Clautiaux ,
Aziz Moukrim ,
Stéphane Nègre  and
Jacques Carlier
François Clautiaux
Affiliation:
Laboratoire HeuDiaSyC, UMR CNRS 6599, UTC, BP 20529, 60205 Compiègne, France; [email protected]., [email protected]., [email protected].
Aziz Moukrim
Affiliation:
Laboratoire HeuDiaSyC, UMR CNRS 6599, UTC, BP 20529, 60205 Compiègne, France; [email protected]., [email protected]., [email protected].
Stéphane Nègre
Affiliation:
Laboratoire de Recherche en Informatique d'Amiens, INSSET, 48 rue Raspail, 02100 St Quentin, France; [email protected].
Jacques Carlier
Affiliation:
Laboratoire HeuDiaSyC, UMR CNRS 6599, UTC, BP 20529, 60205 Compiègne, France; [email protected]., [email protected]., [email protected].
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Abstract

The notion of treewidth is of considerable interest in relation to NP-hard problems.Indeed, several studies have shown that the tree-decomposition method can be used to solve many basic optimization problems in polynomialtime when treewidth is bounded, even if, for arbitrary graphs, computingthe treewidth is NP-hard.Several papers present heuristics with computational experiments.For many graphs the discrepancy between the heuristic resultsand the best lower bounds is still very large. The aim of this paper is to propose two new methodsfor computing the treewidth of graphs: a heuristic and a metaheuristic.The heuristic returns good results in a short computation time,whereas the metaheuristic (a Tabu search method)returns the best results known to have been obtained so far for all the DIMACS vertex coloring / treewidth benchmarks (a well-known collection of graphs used for both vertex coloring and treewidth problems.) Our results actually improve on the previous best results for treewidth problems in 53% of the cases. Moreover, we identify properties of the triangulation processto optimize the computing time of our method.

Keywords

Treewidthelimination orderingstriangulated graphsheuristicmetaheuristiccomputational experiments.
Type
Research Article
Information
RAIRO - Operations Research , Volume 38 , Issue 1 , January 2004 , pp. 13 - 26
Copyright
© EDP Sciences, 2004

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