ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
GRASP: A Search Algorithm for Propositional Satisfiability
IEEE Transactions on Computers
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
ACSC '02 Proceedings of the twenty-fifth Australasian conference on Computer science - Volume 4
Proving Consistency Assertions for Automotive Product Data Management
Journal of Automated Reasoning
Proceedings of the conference on Design, automation and test in Europe
Efficient SAT-based bounded model checking for software verification
Theoretical Computer Science
A lightweight component caching scheme for satisfiability solvers
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Adaptive restart strategies for conflict driven SAT solvers
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
A decision-making procedure for resolution-based SAT-solvers
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
A new method for solving hard satisfiability problems
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Determinization of resolution by an algorithm operating on complete assignments
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
SAT in bioinformatics: making the case with haplotype inference
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Beyond unit propagation in SAT solving
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
An overview of parallel SAT solving
Constraints
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Many state-of-the-art SAT solvers use the VSIDS heuristic to make branching decisions based on the activity of variables or literals. In combination with rapid restarts and phase saving this yields a powerful decision heuristic in practice. However, there are approaches that motivate more in-depth reasoning to guide the search of the SAT solver. But more reasoning often requires more information and comes along with more complex data structures. This may sometimes even cause strong concepts to be inapplicable in practice. In this paper we present a suitable data structure for the DMRP approach to overcome the problem above. Moreover, we show how DMRP can be combined with CDCL solving to be competitive to state-of-the-art solvers and to even improve on some families of industrial instances.