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Efficient SAT-Encoding of Linear CSP Constraints
2014
International Symposium on Artificial Intelligence and Mathematics
Propositional satisfiability solving (SAT) has been considerably successful in numerous industrial applications. Whereas the speed and the capacity of SAT solvers significantly improved in the last two decades, the understanding of SAT encodings is still limited and often challenging. Two wellknown variable encodings, namely the order encoding and the sparse encoding, are the most widely used and successfully applied to translate constraint satisfaction problems (CSPs) to equivalent SAT
dblp:conf/isaim/BarahonaHN14
fatcat:5s3qy7mtyrdlvfqzqoidr6pozm