Abstract
In this chapter we introduce a modeling framework based on dynamic programming to compile exact decision diagrams. We describe how dynamic programming models can be used in a top-down compilation method to construct exact decision diagrams. We also present an alternative compilation method based on constraint separation. We illustrate our framework on a number of classical combinatorial optimization problems: maximum independent set, set covering, set packing, single machine scheduling, maximum cut, and maximum 2-satisfiability.
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© 2016 Springer International Publishing Switzerland
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Bergman, D., Cire, A.A., van Hoeve, WJ., Hooker, J. (2016). Exact Decision Diagrams. In: Decision Diagrams for Optimization. Artificial Intelligence: Foundations, Theory, and Algorithms. Springer, Cham. https://doi.org/10.1007/978-3-319-42849-9_3
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DOI: https://doi.org/10.1007/978-3-319-42849-9_3
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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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