Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
Generic ILP versus specialized 0-1 ILP: an update
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
A fast pseudo-boolean constraint solver
Proceedings of the 40th annual Design Automation Conference
Pueblo: A Modern Pseudo-Boolean SAT Solver
Proceedings of the conference on Design, Automation and Test in Europe - Volume 2
A logical approach to efficient Max-SAT solving
Artificial Intelligence
Algorithms for maximum satisfiability using unsatisfiable cores
Proceedings of the conference on Design, automation and test in Europe
Solving (Weighted) Partial MaxSAT through Satisfiability Testing
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
New inference rules for Max-SAT
Journal of Artificial Intelligence Research
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
Exploiting inference rules to compute lower bounds for MAX-SAT solving
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Structural relaxations by variable renaming and their compilation for solving MinCostSAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Towards more effective unsatisfiability-based maximum satisfiability algorithms
SAT'08 Proceedings of the 11th 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
Search pruning techniques in SAT-based branch-and-bound algorithms for the binate covering problem
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
DALculus: theory and tool for development assurance level allocation
SAFECOMP'11 Proceedings of the 30th international conference on Computer safety, reliability, and security
MEDI'11 Proceedings of the First international conference on Model and data engineering
Parallel search for maximum satisfiability
AI Communications - 18th RCRA International Workshop on “Experimental evaluation of algorithms for solving problems with combinatorial explosion”
An empirical study of encodings for group MaxSAT
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
Artificial Intelligence
A new look at BDDs for Pseudo-Boolean constraints
Journal of Artificial Intelligence Research
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Recently, several unsatisfiability-based algorithms have been proposed for Maximum Satisfiability (MaxSAT) and other Boolean Optimization problems. These algorithms are based on being able to iteratively identify and relax unsatisfiable sub-formulas with the use of fast Boolean satisfiability solvers. It has been shown that this approach is very effective for several classes of instances, but it can perform poorly on others for which classical Boolean optimization algorithms find it easy to solve. This paper proposes the use of Pseudo-Boolean Optimization (PBO) solvers as a preprocessor for unsatisfiability-based algorithms in order to increase its robustness. Moreover, the use of constraint branching, a well-known technique from Integer Linear Programming, is also proposed into the unsatisfiability-based framework. Experimental results show that the integration of these features in an unsatisfiability-based algorithm results in an improved and more effective solver for Boolean optimization problems.