Description:
2000 purple & gray hardcover in like new condition; slight wear to covers, no marks inside. US media mail for shipping. A pioneering look at the fundamental role of logic in optimization and constraint satisfactionWhile recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible modeling and solution techniques. Designed to be easily accessible to industry professionals and academics in both operations research and artificial intelligence, the book provides a wealth of examples as well as elegant techniques and modeling frameworks ready for implementation. Timely, original, and…
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Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction Hardcover - 2000 - 1st Edition
by John Hooker
First line
Logical inference is inseparable from optimization.
From the rear cover
A pioneering look at the fundamental role of logic in optimization and constraint satisfaction
While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible modeling and solution techniques. Designed to be easily accessible to industry professionals and academics in both operations research and artificial intelligence, the book provides a wealth of examples as well as elegant techniques and modeling frameworks ready for implementation. Timely, original, and thought-provoking, Logic-Based Methods for Optimization:* Demonstrates the advantages of combining the techniques in problem solving
* Offers tutorials in constraint satisfaction/constraint programming and logical inference
* Clearly explains such concepts as relaxation, cutting planes, nonserial dynamic programming, and Bender's decomposition
* Reviews the necessary technologies for software developers seeking to combine the two techniques
* Features extensive references to important computational studies
* And much more
Details
- Title Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction
- Author John Hooker
- Binding Hardcover
- Edition number 1st
- Edition 1
- Pages 520
- Volumes 1
- Language ENG
- Publisher Wiley-Interscience
- Date 2000-05-30
- Illustrated Yes
- Features Bibliography, Illustrated, Index
- ISBN 9780471385219 / 0471385212
- Weight 1.83 lbs (0.83 kg)
- Dimensions 9.6 x 5.92 x 1.19 in (24.38 x 15.04 x 3.02 cm)
- Library of Congress subjects Mathematical optimization, Logic, Symbolic and mathematical
- Library of Congress Catalog Number 99088732
- Dewey Decimal Code 519.72
Media reviews
Citations
- Choice, 03/01/2001, Page 1304
- Scitech Book News, 12/01/2000, Page 125
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Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction
by John Hooker
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Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction
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Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction
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Logic-Based Methods for Optimization
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Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction
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