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Compact-MDD: Efficiently Filtering(s) MDD Constraints with Reversible Sparse Bit-sets

机译:Compact-MDD:用可逆稀疏位集有效过滤(S)MDD约束

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Multi-Valued Decision Diagrams (MDDs) are instrumental 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 diagrams 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.
机译:多值决策图(MDDS)是用约束编程建模组合问题的乐器。在本文中,我们提出了一种称为SMDD(半MDD)的相关数据结构,其中图中的中心层是非确定性的。我们表明,将任何表(元组集)转换为SMDD很容易和有效。我们还引入了一种新的过滤算法,称为Compact-MDD,基于位操作,并且可以应用于MDD和SMDD。我们的实验结果表明了我们方法的实际兴趣。

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