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In this thesis, we study several algorithms for enforcing Generalized Arc-Consistency (GAC), which is the most popular consistency property for solving Constraint Satisfaction Problems (CSPs) with backtrack search. The popularity of such algorithms stems from their relative low cost and effectiveness in improving the performance of search. Virtually all commercial and public- domain constraint solvers include some implementation of a generic GAC algorithm. In recent years, several algorithms for enforcing GAC have been proposed in the literature that relies on increasingly complex data structures and mechanisms to improve performance. In this thesis, we study, assess, and compare a basic algorithm for generic constraints (i.e., GAC2001), new algorithms for table constraints (i.e., STR1, STR2, STR3, eSTR1, eSTR2, and STRNi), and an algorithm for constraints expressed as multivalued decision diagram (i.e., mddc). We explain the mechanisms of the above algorithms, and empirically evaluate and compare their performances. We propose a new hybrid algorithm that uses a selection criterion to combine the use of STR1 and STRNi.
Adviser: Berthe Y. Choueiry