An extension of complexity bounds and dynamic heuristics for tree-decompositions of CSP

Authors:
Philippe Jégou;Samba Ndojh Ndiaye;Cyril Terrioux
Affiliations:
LSIS – UMR CNRS 6168, Université Paul Cézanne (Aix-Marseille 3), Marseille, France;LSIS – UMR CNRS 6168, Université Paul Cézanne (Aix-Marseille 3), Marseille, France;LSIS – UMR CNRS 6168, Université Paul Cézanne (Aix-Marseille 3), Marseille, France
Venue:
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Year:
2006

Citing 4
Cited 0

Simple linear-time algorithms to test chordality of graphs, test acyclicity of hypergraphs, and selectively reduce acyclic hypergraphs

SIAM Journal on Computing
Tree clustering for constraint networks (research note)

Artificial Intelligence
A comparison of structural CSP decomposition methods

Artificial Intelligence
Hybrid backtracking bounded by tree-decomposition of constraint networks

Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper deals with methods exploiting tree-decomposition approaches for solving constraint networks. We consider here the practical efficiency of these approaches by defining five classes of variable orders more and more dynamic which guarantee time complexity bounds from O(exp(w+1)) to O(exp(2(w+k))), with w the ”tree-width” of a CSP and k a constant. Finally, we assess practically their relevance.