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

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. © 2006 Elsevier B.V. All rights reserved.