Articoli correlati a Logic-Based Methods for Optimization: Combining Optimization...
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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
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
JOHN HOOKER, PhD, is Professor of Operations Research and T. Jerome Holleran Professor of Business Ethics and Social Responsibility at the Graduate School of Industrial Administration, Carnegie Mellon University. Well-known for his work in the operations research/computer science interface, Dr. Hooker has published over 80 articles and coauthored (with Vijay Chandru) Optimization Methods for Logical Inference, also available from Wiley.
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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
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreWiley-Interscience
- Data di pubblicazione2000
- ISBN 10 0471385212
- ISBN 13 9780471385219
- RilegaturaCopertina rigida
- LinguaInglese
- Numero di pagine495
- Contatto del produttorenon disponibile
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Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction
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ISBN 10: 0471385212
ISBN 13: 9780471385219
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Gebunden. Condizione: New. This is a book that should be widely read by graduate students and researchers in both the computer science and optimization communities. (Choice, Vol. 38, No. 7, March 2001) Goal is to broaden the conceptual foundations of optimization to include logical. Codice articolo 446916281
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Logic-Based Methods for Optimization : Combining Optimization and Constraint Satisfaction
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ISBN 13: 9780471385219
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Logic-Based Methods for Optimization : Combining Optimization and Constraint Satisfaction
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Wiley-Interscience, 2000
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ISBN 13: 9780471385219
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Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction
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ISBN 13: 9780471385219
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Buch. Condizione: Neu. Neuware - Dieser Band untersucht die Rolle der Logik bei der Optimierung - Grundlage für eine neue Generation von Vorlesungen in diskreter Optimierung! In ausgesprochen klarem, technisch sauberen Stil werden Tools und Techniken erläutert sowie vielfältige Programmieroptionen (ILOG, CPLEX, OPL, AMPL, GAMS und andere). Mit zahlreichen anschaulichen Beispielen. (07/00). Codice articolo 9780471385219
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