Abstract
This is the first of three chapters that apply decision diagrams in the context of constraint programming. This chapter starts by providing a background of the solving process of constraint programming, focusing on consistency notions and constraint propagation. We then extend this methodology to MDD-consistency and MDD-based constraint propagation. We present MDD propagation algorithms for specific constraint types, including linear inequalities, ALLDIFFERENT, AMONG, and ELEMENT constraints, and experimentally demonstrate how MDD propagation can improve conventional domain propagation.
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© 2016 Springer International Publishing Switzerland
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Bergman, D., Cire, A.A., van Hoeve, WJ., Hooker, J. (2016). MDD-Based Constraint Programming. In: Decision Diagrams for Optimization. Artificial Intelligence: Foundations, Theory, and Algorithms. Springer, Cham. https://doi.org/10.1007/978-3-319-42849-9_9
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DOI: https://doi.org/10.1007/978-3-319-42849-9_9
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42847-5
Online ISBN: 978-3-319-42849-9
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