Affiliation:
1. U. R. PRINCE de l'ISITCom de Hammam Sousse, Tunisia
2. Faculty of Sciences, University of Monastir, Tunisia
Abstract
Many combinatorial problems can be formulated as Valued Constraint Satisfaction Problems (VCSPs). In this framework, the constraints are defined by means of valuation functions to reflect several degrees of coherence. Despite the NP-hardness of the VCSP, tractable versions can be obtained by forcing the allowable valuation functions to have specific features. This is the case for submodular VCSPs, i.e. VCSPs that involve submodular valuation functions only. In this paper, we propose a problem decomposition scheme for binary VCSPs that takes advantage of submodular functions even when the studied problem is not submodular. The proposed scheme consists in decomposing the problem to be solved into a set of submodular, then tractable, subproblems. The decomposition scheme combines two techniques that where already used in the framework of constraint-based reasoning, but in separate manner. These techniques are domain partitioning and value permutation.
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Artificial Intelligence
Cited by
1 articles.
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1. Soft Directional Substitutable based Decompositions for MOVCSP;Proceedings of the 10th International Conference on Operations Research and Enterprise Systems;2021