Efficient local search for very large-scale satisfiability problems
ACM SIGART Bulletin
Free bits, PCPs and non-approximability-towards tight results
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Performance test of local search algorithms using new types of random CNF formulas
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Systematic versus stochastic constraint satisfaction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Adding new clauses for faster local search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Weighting for godot: learning heuristics for GSAT
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
sub-SAT: a formulation for relaxed boolean satisfiability with applications in routing
Proceedings of the 2002 international symposium on Physical design
A Two Level Local Search for MAX-SAT Problems with Hard and Soft Constraints
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Efficient 2 and 3-Flip Neighborhood Search Algorithms for the MAX SAT
COCOON '98 Proceedings of the 4th Annual International Conference on Computing and Combinatorics
Parallelizing Local Search for CNF Satisfiability Using Vectorization and PVM
WAE '00 Proceedings of the 4th International Workshop on Algorithm Engineering
Exploiting Partial Knowledge of Satisfying Assignments
WAE '01 Proceedings of the 5th International Workshop on Algorithm Engineering
A Constraint Directed Model for Partial Constraint Satisfaction Problems
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Parallelizing local search for CNF satisfiability using vectorization and PVM
Journal of Experimental Algorithmics (JEA)
A two-phase backbone-based search heuristic for partial MAX-SAT: an initial investigation
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
An effective heuristic algorithm for the maximum satisfiability problem
Applied Intelligence
Exact Max-SAT solvers for over-constrained problems
Journal of Heuristics
Exploiting partial knowledge of satisfying assignments
Discrete Applied Mathematics
Logic programming with satisfiability
Theory and Practice of Logic Programming
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
Partial max-SAT solvers with clause learning
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
MiniMaxSAT: a new weighted Max-SAT solver
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
A satisfiability-based approach for embedding generalized tanglegrams on level graphs
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
A backbone-based co-evolutionary heuristic for partial MAX-SAT
EA'05 Proceedings of the 7th international conference on Artificial Evolution
Solving over-constrained problems with SAT technology
SAT'05 Proceedings of the 8th 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
Generalized k-ary tanglegrams on level graphs: A satisfiability-based approach and its evaluation
Discrete Applied Mathematics
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MAXSAT solutions, i.e., near-satisfying assignments for propositional formulas, are sometimes meaningless for real-world problems because such formulas include "mandatory clauses" that must be all satisfied for the solution to be reasonable. In this paper, we introduce Partial MAXSAT and investigate how to solve it using local search algorithms. An instance of Partial MAXSAT consists of two formulas fA and fB, and its solution must satisfy all clauses in fA and as many clauses in fB as possible. The basic idea of our algorithm is to give weight to fA-clauses (the mandatory clauses) and then apply local search. We face two problems; (i) what amount of weight is appropriate and (ii) how to deal with the common action of local search algorithms, giving weight to clauses for their own purpose, which will hide the initial weight as the algorithms proceed.