Authors:
Abdelmalek Ait-Amokhtar
1
;
Kamal Amroun
1
and
Zineb Habbas
2
Affiliations:
1
University of Bejaia, Algeria
;
2
LITA, France
Keyword(s):
CSP, Structural decompositions, Hypertree decomposition, Acyclic Solving algorithm, Enumerative search.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Computational Intelligence
;
Constraint Satisfaction
;
Enterprise Information Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
;
Symbolic Systems
Abstract:
This paper deals with the structural decomposition methods and their use for solving Constraint Satisfaction problems (CSP). mong the numerous structural decomposition methods, hypertree decomposition has been shown to be the most general CSP decomposition. However so far the exact methods are not able to find optimal decomposition of realistic instances in a reasonable CPU time. We present Alea, a new heuristic to compute hypertree decomposition. Some experiments on a serial of benchmarks coming from the literature or the industry permit us to observe that Alea is in general better or comparable to BE (Bucket Elimination), the best well known heuristic, while it generally outperforms DBE (Dual Bucket Elimination), another successful heuristic. We also experiment an algorithm (acyclic solving algorithm) for solving an acyclic CSP obtained by using the heuristic Alea. The experimental results we obtain are promising comparing to those obtained by solving CSP using an enumerative
search algorithm.
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