Computational Optimization and Applications
Maintenance scheduling problems as benchmarks for constraint algorithms
Annals of Mathematics and Artificial Intelligence
Using weighted MAX-SAT engines to solve MPE
Eighteenth national conference on Artificial intelligence
Optimal Protein Structure Alignment Using Maximum Cliques
Operations Research
Artificial Intelligence
Improved Design Debugging Using Maximum Satisfiability
FMCAD '07 Proceedings of the Formal Methods in Computer Aided Design
Algorithms for maximum satisfiability using unsatisfiable cores
Proceedings of the conference on Design, automation and test in Europe
Symmetry Breaking for Maximum Satisfiability
LPAR '08 Proceedings of the 15th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning
Solving (Weighted) Partial MaxSAT through Satisfiability Testing
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Exploiting Cycle Structures in Max-SAT
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Algorithms for Weighted Boolean Optimization
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Within-problem learning for efficient lower bound computation in Max-SAT solving
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
MiniMaxSAT: a new weighted Max-SAT solver
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Towards more effective unsatisfiability-based maximum satisfiability algorithms
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
Solving MAXSAT by solving a sequence of simpler SAT instances
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Exploiting Cardinality Encodings in Parallel Maximum Satisfiability
ICTAI '11 Proceedings of the 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence
Mapping problems with finite-domain variables to problems with boolean variables
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
Boolean lexicographic optimization: algorithms & applications
Annals of Mathematics and Artificial Intelligence
Improving unsatisfiability-based algorithms for boolean optimization
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
On solving the partial MAX-SAT problem
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
sub-SAT: a formulation for relaxed Boolean satisfiability with applications in routing
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Improving SAT-Based weighted MaxSAT solvers
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Concept adjustment for description logics
Proceedings of the seventh international conference on Knowledge capture
A Markov logic framework for recognizing complex events from multimodal data
Proceedings of the 15th ACM on International conference on multimodal interaction
A modular approach to MaxSAT modulo theories
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
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Many industrial optimization problems can be translated to MaxSAT. Although the general problem is NP hard, like SAT, many practical problems may be solved using modern MaxSAT solvers. In this paper we present several algorithms specially designed to deal with industrial or real problems. All of them are based on the idea of solving MaxSAT through successive calls to a SAT solver. We show that this SAT-based technique is efficient in solving industrial problems. In fact, all state-of-the-art MaxSAT solvers that perform well in industrial instances are based on this technique. In particular, our solvers won the 2009 partial MaxSAT and the 2011 weighted partial MaxSAT industrial categories of the MaxSAT evaluation. We prove the correctness of all our algorithms. We also present a complete experimental study comparing the performance of our algorithms with latest MaxSAT solvers.