Logic-Based Methods for Optimization

Combining Optimization and Constraint Satisfaction

Autor: John Hooker

Język:

Oprawa: Twarda

Wydawca: John Wiley & Sons Inc

Dostępność: Dostępna u dostawcy

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A pioneering look at the fundamental role of logic in optimization and constraint satisfaction While...

Informacje o książce

Autor

John Hooker

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

2000

strony

520

EAN

9780471385219

ISBN

0471385212

Enbook ID

04890350

Wydawca

John Wiley & Sons Inc

Waga

972

Wymiary

165 x 240 x 34

Pełny opis

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

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Combining Optimization and Constraint Satisfaction

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