Improving WPM2 for (Weighted) Partial MaxSAT

• Published in: Principles and Practice of Constraint Programming pp. 117 - 132
• Main Authors: Ansótegui, Carlos, Bonet, Maria Luisa, Gabàs, Joel, Levy, Jordi
• Format: Book Chapter Publication
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2013; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Combinatorial optimization problems; Constraint programming (Computer science); Experimental evaluation; Informàtica; Linear Integer Arithmetic; Max-SAT; MaxSAT Algorithm; MaxSAT Problem; New approaches; Optimality; Partial MaxSAT; Programació; Programació per restriccions (Informàtica); Satisfiability problems; Smt solvers; Soft Clause; Subformulas; Àrees temàtiques de la UPC
• ISBN: 9783642406263; 3642406262
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-40627-0_12

Weighted Partial MaxSAT (WPMS) is an optimization variant of the Satisfiability (SAT) problem. Several combinatorial optimization problems can be translated into WPMS. In this paper we extend the state-of-the-art WPM2 algorithm by adding several improvements, and implement it on top of an SMT solver. In particular, we show that by focusing search on solving to optimality subformulas of the original WPMS instance we increase the efficiency of WPM2. From the experimental evaluation we conducted on the PMS and WPMS instances at the 2012 MaxSAT Evaluation, we can conclude that the new approach is both the best performing for industrial instances, and for the union of industrial and crafted instances.