The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Compiling finite linear CSP into SAT
Constraints
Improving resource-unaware SAT solvers
LPAR'10 Proceedings of the 17th international conference on Logic for programming, artificial intelligence, and reasoning
The modeling power of the periodic event scheduling problem: railway timetables-and beyond
ATMOS'04 Proceedings of the 4th international Dagstuhl, ATMOS conference on Algorithmic approaches for transportation modeling, optimization, and systems
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
A compact encoding of pseudo-boolean constraints into SAT
KI'12 Proceedings of the 35th Annual German conference on Advances in Artificial Intelligence
Soundness of inprocessing in clause sharing SAT solvers
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
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In this paper, periodic event scheduling problems (PESP) are encoded as satisfiability problems (SAT) and solved by a state-of-the-art SAT solver. Two encodings, based on direct and order encoded domains, are presented. An experimental evaluation suggests that the SAT-based approach using order encoding outperforms constraint-based PESP solvers, which until now were considered to be the best solvers for PESP. This opens the possibility to model significantly larger real-world problems.