Logic-based methods for optimization: combining optimization and constraint satisfaction

By: Hooker, John
Material type: TextTextSeries: Wiley-interscience series in discrete mathematics and optimizationPublisher: New York John Wiley & Sons, Inc. 2000Description: xvi, 495 p.ISBN: 9780471385219Subject(s): Logic, Symbolic and mathematical | Linear programming | Mathematical optimizationDDC classification: 519.72 Summary: 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: (http://as.wiley.com/WileyCDA/WileyTitle/productCd-0471385212.html)
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Slot 1682 (2 Floor, East Wing) Non-fiction 519.72 H6L6 (Browse shelf) Available 176158

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: (http://as.wiley.com/WileyCDA/WileyTitle/productCd-0471385212.html)

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