This paper deals with three solvers for combinatorial problems: the commercial state-of-the-art solver Ilog OPL, and the research ASP systems DLV and SMODELS. The first goal of this research is to evaluate the relative performance of such systems, using a reproducible and extensible experimental methodology. In particular, we consider a third-party problem library, i.e., the CSPLib, and uniform rules for modelling and selecting instances. The second goal is to analyze the effects of a popular reformulation technique, i.e., symmetry breaking, and the impact of other modelling aspects, like global constraints and auxiliary predicates. Results show that there is not a single solver winning on all problems, and that reformulation is almost always beneficial: symmetry-breaking may be a good choice, but its complexity has to be carefully chosen, by taking into account also the particular solver used. Global constraints often, but not always, help OPL, and the addition of auxiliary predicates is usually worth, especially when dealing with ASP solvers. Moreover, interesting synergies among the various modelling techniques exist.
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