Regular-SAT: A many-valued approach to solving combinatorial problems

Authors:
Ramón Béjar;Felip Manyí;Alba Cabiscol;Cèsar Ferníndez;Carla Gomes
Affiliations:
Department of Computer Science, Universitat de LLeida, Jaume II 69, 25001 LLeida, Spain;IIIA, Artificial Intelligence Research Institute,CSIC, Spanish Council for Scientific Research,Campus UAB, 08193 Bellaterra, Spain;Department of Computer Science, Universitat de LLeida, Jaume II 69, 25001 LLeida, Spain;Department of Computer Science, Universitat de LLeida, Jaume II 69, 25001 LLeida, Spain;Department of Computer Science, Cornell University, Ithaca, NY 14853, USA
Venue:
Discrete Applied Mathematics
Year:
2007

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Abstract

Regular-SAT is a constraint programming language between CSP and SAT that-by combining many of the good properties of each paradigm-offers a good compromise between performance and expressive power. Its similarity to SAT allows us to define a uniform encoding formalism, to extend existing SAT algorithms to Regular-SAT without incurring excessive overhead in terms of computational cost, and to identify phase transition phenomena in randomly generated instances. On the other hand, Regular-SAT inherits from CSP more compact and natural encodings that maintain more the structure of the original problem. Our experimental results-using a range of benchmark problems-provide evidence that Regular-SAT offers practical computational advantages for solving combinatorial problems.