In recent years, portfolio approaches to solving SAT problems and CSPs have become increasingly common. There are also a number of different techniques for converting SAT problems into CSPs. In this paper, we leverage advances in both areas and present a novel hierarchical portfolio-based approach to CSP solving that does not rely purely on CSP solvers, but may convert a problem to SAT choosing a conversion technique and the accommodating SAT solver. Our experimental evaluation relies on competition CSP instances and uses eight CSP solvers, three SAT encodings and eighteen SAT solvers. We demonstrate that significant performance improvements can be obtained by considering alternative view-points of a combinatorial problem.
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