Encoding Selection for Solving Hamiltonian Cycle Problems with ASP

Answer Set Programming (ASP) [3] has been shown to be especia lly effective on search and optimization problems whose decision versions are in the class NP, includ ing many problems of practical interest [9, 6]. Despite the ease of modeling and the demonstrated pot ential of ASP, using it poses challenges. In particular, it is unlikely a single solver will emerge tha t would uniformly outperform other solvers. Consequently, selecting a solver for an instance may mean th e difference between solving the problem within an acceptable time and having the solver run "forever ." To address the problem, solver selection, portfolio solving, and automated solver parameter configur ation have all been extensively studied [17, 10, 14, 16, 12].