Compact-MDD: Efficiently Filtering (s)MDD Constraints with Reversible Sparse Bit-sets
(2018) Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18} — Location: Stockholm, Sweden (13.July.2018)
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- Abstract
- Multi-Valued Decision Diagrams (MDDs) are in- strumental in modeling combinatorial problems with Constraint Programming. In this paper, we propose a related data structure called sMDD (semi-MDD) where the central layer of the dia- grams is non-deterministic. We show that it is easy and efficient to transform any table (set of tuples) into an sMDD. We also introduce a new filtering algorithm, called Compact-MDD, which is based on bitwise operations, and can be applied to both MDDs and sMDDs. Our experimental results show the practical interest of our approach.
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Citations
Verhaeghe, H., Lecoutre, C., & Schaus, P. (2018). Compact-MDD: Efficiently Filtering (s)MDD Constraints with Reversible Sparse Bit-sets. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. Published. Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}, Stockholm, Sweden. https://doi.org/10.24963/ijcai.2018/192