Experimental results on the application of satisfiability algorithms to scheduling problems
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
The OPL optimization programming language
The OPL optimization programming language
Efficiency of a Good But Not Linear Set Union Algorithm
Journal of the ACM (JACM)
Factorizing Equivalent Variable Pairs in ROBDD-Based Implementations of Pos
AMAST '98 Proceedings of the 7th International Conference on Algebraic Methodology and Software Technology
Equivalent literal propagation in the DLL procedure
Discrete Applied Mathematics - The renesse issue on satisfiability
Toward Leaner Binary-Clause Reasoning in a Satisfiability Solver
Annals of Mathematics and Artificial Intelligence
Logic programming with satisfiability
Theory and Practice of Logic Programming
Universal Booleanization of Constraint Models
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Sorting networks and their applications
AFIPS '68 (Spring) Proceedings of the April 30--May 2, 1968, spring joint computer conference
Compiling finite linear CSP into SAT
Constraints
MINION: A Fast, Scalable, Constraint Solver
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Modeling choices in quasigroup completion: SAT vs. CSP
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Circuit complexity and decompositions of global constraints
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
MiniZinc: towards a standard CP modelling language
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
The log-support encoding of CSP into SAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
LPAR'10 Proceedings of the 16th international conference on Logic for programming, artificial intelligence, and reasoning
Optimal base encodings for pseudo-boolean constraints
TACAS'11/ETAPS'11 Proceedings of the 17th international conference on Tools and algorithms for the construction and analysis of systems: part of the joint European conferences on theory and practice of software
Efficient CNF simplification based on binary implication graphs
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
Boolean equi-propagation for optimized SAT encoding
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Coprocessor 2.0: a flexible CNF simplifier
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Compiling finite domain constraints to sat with bee*
Theory and Practice of Logic Programming
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We present an approach to propagation-based SAT encoding of combinatorial problems, Boolean equi-propagation, where constraints are modeled as Boolean functions which propagate information about equalities between Boolean literals. This information is then applied to simplify the CNF encoding of the constraints. A key factor is that considering only a small fragment of a constraint model at one time enables us to apply stronger, and even complete, reasoning to detect equivalent literals in that fragment. Once detected, equivalences apply to simplify the entire constraint model and facilitate further reasoning on other fragments. Equi-propagation in combination with partial evaluation and constraint simplification provide the foundation for a powerful approach to SAT-based finite domain constraint solving. We introduce a tool called BEE (Ben-Gurion Equi-propagation Encoder) based on these ideas and demonstrate for a variety of benchmarks that our approach leads to a considerable reduction in the size of CNF encodings and subsequent speed-ups in SAT solving times.