Genetic algorithms engineering optimization par gen mitsuo (22 résultats)

Etat : very_good. Book is in very good condition and may include minimal underlining highlighting. The book can also include "From the library of" labels. May not contain miscellaneous items toys, dvds, etc. . We offer 100% money back guarantee and 24 7 customer service.

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Hardcover. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

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Hardcover. Etat : New. Brand New Hardcover Book, Crisp and Clean.

Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,950grams, ISBN:9780471315315.

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Etat : new.

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

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New. In English.

Gebundene Ausgabe. Etat : Sehr gut. Auflage: 1. 512 Seiten Cover etwas berieben, kleine Lagerspuren am Buch, Inhalt einwandfrei und ungelesen Sprache: Englisch Gewicht in Gramm: 870.

Etat : New. pp. xvi + 495 Illus.

Hardback. Etat : New. A comprehensive guide to a powerful new analytical tool by two of its foremost innovators The past decade has witnessed many exciting advances in the use of genetic algorithms (GAs) to solve optimization problems in everything from product design to scheduling and client/server networking. Aided by GAs, analysts and designers now routinely evolve solutions to complex combinatorial and multiobjective optimization problems with an ease and rapidity unthinkable withconventional methods. Despite the continued growth and refinement of this powerful analytical tool, there continues to be a lack of up-to-date guides to contemporary GA optimization principles and practices. Written by two of the world's leading experts in the field, this book fills that gap in the literature. Taking an intuitive approach, Mitsuo Gen and Runwei Cheng employ numerous illustrations and real-world examples to help readers gain a thorough understanding of basic GA concepts-including encoding, adaptation, and genetic optimizations-and to show how GAs can be used to solve an array of constrained, combinatorial, multiobjective, and fuzzy optimization problems. Focusing on problems commonly encountered in industry-especially in manufacturing-Professors Gen and Cheng provide in-depth coverage of advanced GA techniques for: * Reliability design * Manufacturing cell design * Scheduling * Advanced transportation problems * Network design and routing Genetic Algorithms and Engineering Optimization is an indispensable working resource for industrial engineers and designers, as well as systems analysts, operations researchers, and management scientists working in manufacturing and related industries. It also makes an excellent primary or supplementary text for advanced courses in industrial engineering, management science, operations research, computer science, and artificial intelligence.…

Etat : New. Genetic algorithms are probabilistic search techniques based on the principles of biological evolution. As a biological organism evolves to more fully adapt to its environment, a genetic algorithm follows a path of analysis from which a design evolves, one that is optimal for the environmental constraints placed upon it. Series: Engineering Design and Automation. Num Pages: 512 pages, Ill. BIC Classification: TCBG; TGPC. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 164 x 242 x 35. Weight in Grams: 884. . 1999. 1st Edition. Hardcover. . . . .…

Etat : New. pp. xvi + 495.

Etat : New. Genetic algorithms are probabilistic search techniques based on the principles of biological evolution. As a biological organism evolves to more fully adapt to its environment, a genetic algorithm follows a path of analysis from which a design evolves, one that is optimal for the environmental constraints placed upon it. Series: Engineering Design and Automation. Num Pages: 512 pages, Ill. BIC Classification: TCBG; TGPC. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 164 x 242 x 35. Weight in Grams: 884. . 1999. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Hardback. Etat : New. A comprehensive guide to a powerful new analytical tool by two of its foremost innovators The past decade has witnessed many exciting advances in the use of genetic algorithms (GAs) to solve optimization problems in everything from product design to scheduling and client/server networking. Aided by GAs, analysts and designers now routinely evolve solutions to complex combinatorial and multiobjective optimization problems with an ease and rapidity unthinkable withconventional methods. Despite the continued growth and refinement of this powerful analytical tool, there continues to be a lack of up-to-date guides to contemporary GA optimization principles and practices. Written by two of the world's leading experts in the field, this book fills that gap in the literature. Taking an intuitive approach, Mitsuo Gen and Runwei Cheng employ numerous illustrations and real-world examples to help readers gain a thorough understanding of basic GA concepts-including encoding, adaptation, and genetic optimizations-and to show how GAs can be used to solve an array of constrained, combinatorial, multiobjective, and fuzzy optimization problems. Focusing on problems commonly encountered in industry-especially in manufacturing-Professors Gen and Cheng provide in-depth coverage of advanced GA techniques for: * Reliability design * Manufacturing cell design * Scheduling * Advanced transportation problems * Network design and routing Genetic Algorithms and Engineering Optimization is an indispensable working resource for industrial engineers and designers, as well as systems analysts, operations researchers, and management scientists working in manufacturing and related industries. It also makes an excellent primary or supplementary text for advanced courses in industrial engineering, management science, operations research, computer science, and artificial intelligence.…