Abstract
Weighted Partial MaxSAT (WPMS) is a well-known optimization variant of Boolean Satisfiability (SAT) that finds a wide range of practical applications. WPMS divides the formula in two sets of clauses: The hard clauses that must be satisfied and the soft clauses that can be unsatisfied with a penalty given by their associated weight. However, some applications may require each constraint to be modeled as a set or group of clauses. The resulting formalism is referred to as Group MaxSAT. This paper overviews Group maxSAT, and shows how several optimization problems can be modeled as Group MaxSAT. Several encodings from Group MaxSAT to standard MaxSAT are formalized and refined. A comprehensive empirical study compares the performance of several MaxSAT solvers with the proposed encodings. The results indicate that, depending on the underlying MaxSAT solver and problem domain, the solver may perform better with a given encoding than with the others.
This work was partially supported by SFI PI grant BEACON (09/IN.1/I2618).
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Heras, F., Morgado, A., Marques-Silva, J. (2012). An Empirical Study of Encodings for Group MaxSAT. In: Kosseim, L., Inkpen, D. (eds) Advances in Artificial Intelligence. Canadian AI 2012. Lecture Notes in Computer Science(), vol 7310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30353-1_8
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DOI: https://doi.org/10.1007/978-3-642-30353-1_8
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