Extending Dual Arc Consistency

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Extending Dual Arc Consistency

Comparisons between primal and dual approaches have recently been extensively studied and evaluated from a theoretical standpoint based on the amount of pruning achieved by each of these when applied to non-binary constraint satisfaction problems. Enforcing arc consistency on the dual encoding has been shown to strictly dominate enforcing GAC on the primal encoding (Stergiou & Walsh 1999). More...

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Generalized arc consistency (GAC) is the most widely used local consistency in constraint programming. Several GAC algorithms for specific constraints, as well as generic algorithms that can be used on any constraint, have been proposed in the literature. Stronger local consistencies than GAC have also been studied but algorithms for such consistencies are generally considered too expensive. In...

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Constraint satisfaction problems (CSP's) naturally occur in a number of important industrial applications, such as planning, scheduling and resource allocation. GENET is a neural network simulator to solve binary constraint satisfaction problems. GENET uses a convergence procedure based on a relaxed form of local consistency to nd assignments which are locally minimal in terms of constraint vio...

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| Many important applications, such as graph coloring, scheduling and production planning, can be solved by GENET, a local search method which is used to solve binary constraint satisfaction problems (CSPs). Where complete search methods are typically augmented with consistency methods to reduce the search, local search methods are not. We propose a consistency technique, lazy arc consistency ,...

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ژورنال

عنوان ژورنال: International Journal of Pattern Recognition and Artificial Intelligence

سال: 2003

ISSN: 0218-0014,1793-6381

DOI: 10.1142/s0218001403002654