Eric Monfroy

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Constraint Logic Programming (CLP) is a new class of programming languages combining the declarativity of logic programming with the e ciency of constraint solving. New application areas, amongst them many di erent classes of combinatorial search problems such as scheduling, planning or resource allocation can now be solved, which were intractable for logic(More)
We study here constraint satisfaction problems that are based on predefined, explicitly given finite constraints. To solve them we propose a notion of rule consistency that can be expressed in terms of rules derived from the explicit representation of the initial constraints. This notion of local consistency is weaker than arc consistency for constraints of(More)
In constraint programming, enumeration strategies are crucial for resolution performances. In this work, we model the known NP-complete problems Latin Square, Magic Square and Sudoku as a constraint satisfaction problems. We solve them with constraint programming comparing the performance of different variable and value selection heuristics in its(More)
kB-consistencies form the class of strong consistencies used in interval constraint programming. We survey, prove, and give theoretical motivations to some technical improvements to a naive kBconsistency algorithm. Our contribution is twofold: on the one hand, we introduce an optimal 3Bconsistency algorithm whose time-complexity of O(mdn) improves the known(More)
Set covering problem is the model for many important industrial applications. In this paper, we solve some benchmarks of this problem with ant colony optimization algorithms using a new transition rule. A look-ahead mechanism was incorporated to check constraint consistency in ant computing. Computational results are presented showing the advantages to use(More)