Abstract

Constraint satisfaction problems (CSP) or Boolean satisfiability problem (SAT) are two well-known paradigms to model and solve combinatorial problems. Modeling and resolution of CSP is often strengthened by global constraints (e.g., Alldiff constraint). This paper highlights two different ways of handling specific structural information: a uniform propagation framework to handle (interleaved) Alldiff constraints with some CSP reduction rules and a SAT encoding of these rules that preserves the reduction properties of CSP. We illustrate our approach on the well-known Sudoku puzzle which presents 27 overlapping Alldiff constraints in its 9 × 9 standard size. We also present some preliminary results we obtained in CHR, GeCode and Zchaff. Key words: Boolean satisfiability problem (SAT), computer science, decision support, constraint programming, global constraint, automated reasoning.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.