9780471385219 - Logic-Based Methods for Optimization: Combining Optimization and Constraint Satisfaction di Hooker, John (16 risultati)

Hardcover. Condizione: Very Good. First Edition. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: new.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. In.

Condizione: As New. Unread book in perfect condition.

Condizione: New. Examining the role of logic in optimization as the theme for integration, this volume is designed for courses in optimization, in particular discrete optimization. Much of the emphasis is placed on corporate tools and techniques, including a wide range of programming options. Series: Wiley-Interscience Series in Discrete Mathematics and Optimization. Num Pages: 520 pages, Illustrations. BIC Classification: PBU. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 243 x 161 x 29. Weight in Grams: 889. . 2000. 1st Edition. Hardcover. . . . .

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.

Hardcover. Condizione: Brand New. 1st edition. 495 pages. 9.25x6.25x1.25 inches. In Stock.

Condizione: New. Examining the role of logic in optimization as the theme for integration, this volume is designed for courses in optimization, in particular discrete optimization. Much of the emphasis is placed on corporate tools and techniques, including a wide range of programming options. Series: Wiley-Interscience Series in Discrete Mathematics and Optimization. Num Pages: 520 pages, Illustrations. BIC Classification: PBU. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 243 x 161 x 29. Weight in Grams: 889. . 2000. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Buch. Condizione: Neu. Neuware - 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 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; 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).

hardcover. Condizione: New. In shrink wrap. Looks like an interesting title!

Hardcover. Condizione: new. Hardcover. 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 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condizione: Brand New. 1st edition. 495 pages. 9.25x6.25x1.25 inches. In Stock. This item is printed on demand.