Abstract
This introductory chapter explains the motivation for developing decision diagrams as a new discrete optimization technology. It shows how decision diagrams implement the five main solution strategies of general-purpose optimization and constraint programming methods: relaxation, branching search, constraint propagation, primal heuristics, and intelligent modeling. It presents a simple example to illustrate how decision diagrams can be used to solve an optimization problem. It concludes with a brief outline of the book.
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© 2016 Springer International Publishing Switzerland
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Bergman, D., Cire, A.A., van Hoeve, WJ., Hooker, J. (2016). Introduction. In: Decision Diagrams for Optimization. Artificial Intelligence: Foundations, Theory, and Algorithms. Springer, Cham. https://doi.org/10.1007/978-3-319-42849-9_1
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DOI: https://doi.org/10.1007/978-3-319-42849-9_1
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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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