ISBN: 9780471315315 - genetic algorithms and engineering optimization (engineering design and automation) (17 Ergebnisse)

Zustand: 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.

Zustand: Acceptable. Used - Acceptable. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library with wear and barcode page may have been removed. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Zustand: new.

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

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

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

Zustand: New. In English.

Hardback. Zustand: 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.…

Zustand: New. pp. xvi + 495 Illus.

Zustand: 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. . . . .…

Gebunden. Zustand: New. MITSUO GEN, PhD, is a professor in the Department of Industrial and Information Systems Engineering at the Ashikaga Institute of Technology in Ashikaga, Japan.RUNWEI CHENG, PhD, is an associate professor in the Institute of Systems Engineering at Northeaste.

Hardcover. Zustand: Brand New. 495 pages. 9.25x6.25x1.25 inches. In Stock.

Zustand: 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.…

Buch. Zustand: Neu. Neuware - Im Mittelpunkt dieses Buches steht eines der wichtigsten Optimierungsverfahren der industriellen Ingenieurtechnik: Mit Hilfe genetischer Algorithmen lassen sich Qualität, Design und Zuverlässigkeit von Produkten entscheidend verbessern. Das Verfahren beruht auf der Wahrscheinlichkeitstheorie und lehnt sich an die Prinzipien der biologischen Vererbung an: Die Eigenschaften des Produkts werden, unter Beachtung der äußeren Randbedingungen, schrittweise optimiert. Ein hochaktueller Band international anerkannter Autoren. (03/00).…

Hardback. Zustand: 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.…