On the parallel complexity of discrete relaxation in constraint satisfaction networks
Artificial Intelligence
Experimental results on the application of satisfiability algorithms to scheduling problems
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
A competitive and cooperative approach to propositional satisfiability
Discrete Applied Mathematics - Special issue: Discrete algorithms and optimization, in honor of professor Toshihide Ibaraki at his retirement from Kyoto University
Another look at graph coloring via propositional satisfiability
Discrete Applied Mathematics
Compiling finite linear CSP into SAT
Constraints
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
A comparison of ATMS and CSP techniques
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
The log-support encoding of CSP into SAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
MEDI'11 Proceedings of the First international conference on Model and data engineering
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A Boolean Satisfiability Testing Problem (SAT) is a combinatorial problem to find a Boolean variable assignment which satisfies all given Boolean formulas. Recent performance improvement of SAT technologies makes SAT-based approaches applicable for solving hard and practical combinatorial problems, such as planning, scheduling, hardware/software verification, and constraint satisfaction. Sugar is a SAT-based constraint solver based on a new encoding method called order encoding which was first used to encode job-shop scheduling problems by Crawford and Baker. In the order encoding, a comparison x≤a is encoded by a different Boolean variable for each integer variable x and integer value a. The Sugar solver shows a good performance for a wide variety of problems, and became the winner of the GLOBAL categories in 2008 and 2009 CSP solver competitions. The talk will provide an introduction to modern SAT solvers, SAT encodings, implementation techniques of the Sugar solver, and its performance evaluation.