Decision Diagrams and Dynamic Programming

Binary and multivalued decision diagrams are closely related to dynamic programming (DP) but differ in some important ways. This paper makes the relationship more precise by interpreting the DP state transition graph as a weighted decision diagram and incorporating the state-dependent costs of DP in...

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Bibliographic Details
Published inIntegration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems pp. 94 - 110
Main Author Hooker, John N.
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2013
SeriesLecture Notes in Computer Science
Subjects
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ISBN3642381707
9783642381706
ISSN0302-9743
1611-3349
DOI10.1007/978-3-642-38171-3_7

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Summary:Binary and multivalued decision diagrams are closely related to dynamic programming (DP) but differ in some important ways. This paper makes the relationship more precise by interpreting the DP state transition graph as a weighted decision diagram and incorporating the state-dependent costs of DP into the theory of decision diagrams. It generalizes a well-known uniqueness theorem by showing that, for a given optimization problem and variable ordering, there is a unique reduced weighted decision diagram with “canonical” edge costs. This can lead to simplification of DP models by transforming the costs to canonical costs and reducing the diagram, as illustrated by a standard inventory management problem. The paper then extends the relationship between decision diagrams and DP by introducing the concept of nonserial decision diagrams as a counterpart of nonserial dynamic programming.
Bibliography:Partial support from NSF grant CMMI-1130012 and AFOSR grant FA-95501110180.
ISBN:3642381707
9783642381706
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-38171-3_7