Paperback. Integrated Methods for Optimization integrates the key concepts of Mathematical Programming and Constraint Programming into a unified framework that allows them to be generalized and combined. The unification of MP and CP creates optimization methods that have much greater modeling power, increased computational speed, and a sizeable reduction computational coding. Hence the benefits of this integration are substantial, providing the Applied Sciences with a powerful, high-level modeling solution for optimization problems. As reviewers of the book have noted, this integration along with constraint programming being incorporated into a number of programming languages, brings the field a step closer to being able to simply state a problem and having the computer solve it. John Hooker is a leading researcher in both the Optimization and Constraint Programming research communities. He has been an instrumental principal for this integration, and over the years, he has given numerous presentations and tutorials on the integration of these two areas. It is felt by many in the field that the future Optimization courses will increasingly be taught from this integrated framework. Integrated Methods for Optimization integrates the key concepts of Mathematical Programming and Constraint Programming into a unified framework that allows them to be generalized and combined. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Bibliographic Details

Title: Integrated Methods for Optimization (Paperback)
Publisher: Springer-Verlag New York Inc., New York, NY
Publication Date: 2010
Language: English
ISBN 10: 1441942580
ISBN 13: 9781441942586
Binding: Paperback
Edition: 1st Edition
Condition: new

About this title

Synopsis

Integrated Methods for Optimization integrates the key concepts of Mathematical Programming and Constraint Programming into a unified framework that allows them to be generalized and combined. The unification of MP and CP creates optimization methods that have much greater modeling power, increased computational speed, and a sizeable reduction computational coding. Hence the benefits of this integration are substantial, providing the Applied Sciences with a powerful, high-level modeling solution for optimization problems. As reviewers of the book have noted, this integration along with constraint programming being incorporated into a number of programming languages, brings the field a step closer to being able to simply state a problem and having the computer solve it.

John Hooker is a leading researcher in both the Optimization and Constraint Programming research communities. He has been an instrumental principal for this integration, and over the years, he has given numerous presentations and tutorials on the integration of these two areas. It is felt by many in the field that the future Optimization courses will increasingly be taught from this integrated framework.

About the Author

Prof. Hooker has published two earlier books on the methodologies of Optimization and Constraint Programming. The first was Optimization Methods for Logical Inference (Wiley 1999) and the second was Logic Based Methods for Optimization: Combining Optimization and Constraints Satisfaction (Wiley 2000). This book will be his third book in this evolving area and it is the book that completes the process of integrating these two methodologies into a single set of methods

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