2021
DOI: 10.48550/arxiv.2104.11951
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Improving the filtering of Branch-And-Bound MDD solver (extended)

Xavier Gillard,
Vianney Coppé,
Pierre Schaus
et al.

Abstract: This paper presents and evaluates two pruning techniques to reinforce the efficiency of constraint optimization solvers based on multi-valued decision-diagrams (MDD). It adopts the branch-and-bound framework proposed by Bergman et al. in 2016 to solve dynamic programs to optimality. In particular, our paper presents and evaluates the effectiveness of the local-bound (LocB) and rough upper-bound pruning (RUB). LocB is a new and effective rule that leverages the approximate MDD structure to avoid the exploration… Show more

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