Overview
- Presents a new theoretical and algorithmic approach to discrete optimization
- Authors among leading researchers in this domain
- Useful for researchers and practitioners in discrete optimization and constraint programming
- Includes supplementary material: sn.pub/extras
Part of the book series: Artificial Intelligence: Foundations, Theory, and Algorithms (AIFTA)
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book introduces a novel approach to discrete optimization, providing both theoretical insights and algorithmic developments that lead to improvements over state-of-the-art technology. The authors present chapters on the use of decision diagrams for combinatorial optimization and constraint programming, with attention to general-purpose solution methods as well as problem-specific techniques.
The book will be useful for researchers and practitioners in discrete optimization and constraint programming.
"Decision Diagrams for Optimization is one of the most exciting developments emerging from constraint programming in recent years. This book is a compelling summary of existing results in this space and a must-read for optimizers around the world." [Pascal Van Hentenryck]
Reviews
“This book goes far beyond answering natural questions about how to use Decision Diagrams in Discrete Optimization: it rigorously defines a comprehensive methodology, shows impressive potential from the computational standpoint and highlights unexpected and exciting research venues. A great and inspiring read!” (Andrea Lodi, École Polytechnique de Montréal)
“Decision Diagrams for Optimization is one of the most exciting developments emerging from constraint programming in recent years. This book is a compelling summary of existing results in this space and a must-read for optimizers around the world.” (Pascal Van Hentenryck, University of Michigan)
“This book provides an excellent demonstration of how the concepts and tools of one research community can cross into another, yielding powerful insights and ideas ... The authors show how the main strategies used in discrete optimization, including problem relaxation, branching search, constraint propagation, primal solving, and problem-specific modeling, can be adapted and cast into a decision diagram framework.” (Randal E. Bryant, Carnegie Mellon University)
Authors and Affiliations
Bibliographic Information
Book Title: Decision Diagrams for Optimization
Authors: David Bergman, Andre A. Cire, Willem-Jan van Hoeve, John Hooker
Series Title: Artificial Intelligence: Foundations, Theory, and Algorithms
DOI: https://doi.org/10.1007/978-3-319-42849-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2016
Hardcover ISBN: 978-3-319-42847-5Published: 14 October 2016
Softcover ISBN: 978-3-319-82679-0Published: 16 June 2018
eBook ISBN: 978-3-319-42849-9Published: 01 November 2016
Series ISSN: 2365-3051
Series E-ISSN: 2365-306X
Edition Number: 1
Number of Pages: XII, 254
Number of Illustrations: 79 b/w illustrations
Topics: Artificial Intelligence, Operations Research/Decision Theory, Discrete Optimization, Operations Research, Management Science, Theory of Computation