CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Fast Theta-Subsumption with Constraint Satisfaction Algorithms
Machine Learning
Solving weighted CSP by maintaining arc consistency
Artificial Intelligence
Exact Max-SAT solvers for over-constrained problems
Journal of Heuristics
Solving (Weighted) Partial MaxSAT through Satisfiability Testing
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
Balance and filtering in structured satisfiable problems
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Modelling Max-CSP as partial Max-SAT
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
Cause clue clauses: error localization using maximum satisfiability
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
Improving unsatisfiability-based algorithms for boolean optimization
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
| Hi-index | 0.00 |
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.