Genetic Algorithms and Engineering Design is the only book to cover the most recent technologies and their application to manufacturing, presenting a comprehensive and fully up-to-date treatment of genetic algorithms in industrial ...

Author: Mitsuo Gen

Publisher: John Wiley & Sons

ISBN: 0471127418

Category: Technology & Engineering

Page: 436

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The last few years have seen important advances in the use ofgenetic algorithms to address challenging optimization problems inindustrial engineering. Genetic Algorithms and Engineering Designis the only book to cover the most recent technologies and theirapplication to manufacturing, presenting a comprehensive and fullyup-to-date treatment of genetic algorithms in industrialengineering and operations research. Beginning with a tutorial on genetic algorithm fundamentals andtheir use in solving constrained and combinatorial optimizationproblems, the book applies these techniques to problems in specificareas--sequencing, scheduling and production plans, transportationand vehicle routing, facility layout, location-allocation, andmore. Each topic features a clearly written problem description,mathematical model, and summary of conventional heuristicalgorithms. All algorithms are explained in intuitive, rather thanhighly-technical, language and are reinforced with illustrativefigures and numerical examples. Written by two internationally acknowledged experts in the field,Genetic Algorithms and Engineering Design features originalmaterial on the foundation and application of genetic algorithms,and also standardizes the terms and symbols used in othersources--making this complex subject truly accessible to thebeginner as well as to the more advanced reader. Ideal for both self-study and classroom use, this self-containedreference provides indispensable state-of-the-art guidance toprofessionals and students working in industrial engineering,management science, operations research, computer science, andartificial intelligence. The only comprehensive, state-of-the-arttreatment available on the use of genetic algorithms in industrialengineering and operations research . . . Written by internationally recognized experts in the field ofgenetic algorithms and artificial intelligence, Genetic Algorithmsand Engineering Design provides total coverage of currenttechnologies and their application to manufacturing systems.Incorporating original material on the foundation and applicationof genetic algorithms, this unique resource also standardizes theterms and symbols used in other sources--making this complexsubject truly accessible to students as well as experiencedprofessionals. Designed for clarity and ease of use, thisself-contained reference: * Provides a comprehensive survey of selection strategies, penaltytechniques, and genetic operators used for constrained andcombinatorial optimization problems * Shows how to use genetic algorithms to make production schedules,solve facility/location problems, make transportation/vehiclerouting plans, enhance system reliability, and much more * Contains detailed numerical examples, plus more than 160auxiliary figures to make solution procedures transparent andunderstandable

We summarized the results of related genetic algorithm studies from 1992 to early 1996 in our book Genetic Algorithms and Engineering Design ( New York : John Wiley & Sons , 1997 ) , including the following major topics : con- strained ...

Author: Mitsuo Gen

Publisher: John Wiley & Sons

ISBN: 0471315311

Category: Technology & Engineering

Page: 520

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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.

They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering.

Author: Dipankar Dasgupta

Publisher: Springer Science & Business Media

ISBN: 9783662034231

Category: Computers

Page: 555

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Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference by practitioners to help them apply evolutionary algorithms to problems in their engineering domains.

3rd int . conf . on Genetic algorithms , pp . 191-197 , 1989 56 Dasgupta D. , and McGregor ... 1st int . conf . on Adaptive computing in engineering design and control , Plymouth Engineering Design Centre , UK , 21-22 September , pp .

Author: Ali M. S. Zalzala

Publisher: IET

ISBN: 0852969023

Category: Technology & Engineering

Page: 286

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The contributions presented in this book are extended version of commissioned papers from some of the highest quality contributions to the conference. Chosen for their experience in the field, the authors are drawn from academia and industry worldwide. The chapters cover the main fields of work as well as presenting tutorial material in this important subject, which is currently receiving considerable attention from engineers.

Booker L (1987) Improving search in genetic algorithms. In: Genetic algorithms and simulated annealing. Morgan Kaufmann Publishers, Los Altos, CA, 61–73 5. Cheng R, Gen M (1997) Genetic algorithms & engineering design.

Author: Ali K. Kamrani

Publisher: Springer Science & Business Media

ISBN: 0387958630

Category: Technology & Engineering

Page: 442

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"Engineering Design and Rapid Prototyping" offers insight into the methods and techniques that allow for easily implementing engineering designs by incorporating advanced methodologies and technologies. This book contains advanced topics such as feature-based design and process planning, modularity and rapid manufacturing, along with a collection of the latest methods and technologies currently being utilized in the field. The volume also: -Provides axiomatic design and solution methodologies for both design and manufacturing -Discusses product life cycle development and analysis for ease of manufacture and assembly -Offers applied methods and technologies in rapid prototyping, tooling and manufacturing "Engineering Design and Rapid Prototyping" will be extremely valuable for any engineers and researchers and students working in engineering design.

Genetic Algorithms and Engineering Optimization. Wiley Series in Engineering Design and Automation. John Wiley & Sons, New York, 2000. M. Gen, K. Ida, and J. Kim. A Spanning Tree-Based Genetic Algorithm for Bicriteria Topological ...

Author: Carlos Coello Coello

Publisher: Springer Science & Business Media

ISBN: 9780387367972

Category: Computers

Page: 800

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This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.

Author: David Stuart Todd

Publisher:

ISBN: OCLC:38076115

Category:

Page: 279

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Genetic Algorithms and Engineering Optimization.NewYork, John Wiley & Sons. 9. Gen, M. & Cheng, R. (2003). Evolutionary network design: hybrid genetic algorithms approach. International Journal of Computational Intelligence and ...

Author: Mitsuo Gen

Publisher: Springer Science & Business Media

ISBN: 9781848001817

Category: Technology & Engineering

Page: 692

View: 139

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Network models are critical tools in business, management, science and industry. “Network Models and Optimization” presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing. The book extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, traveling salesman and postman problems, location-allocation problems, project scheduling problems, multistage-based scheduling problems, logistics network problems, communication network problem, and network models in assembly line balancing problems, and airline fleet assignment problems. The book can be used both as a student textbook and as a professional reference for practitioners who use network optimization methods to model and solve problems.

[20]Eshelman, L. J., 1991, The CHCAdaptive Search Algorithm: How to have safe search when engaging in nontraditional genetic recombination, in Rawlins G. (Editor), Foundations of Genetic Algorithms (FOGA2), Morgan Kaufmann, San Mateo, ...

Author: Pravir K. Chawdhry

Publisher: Springer Science & Business Media

ISBN: 9781447104278

Category: Computers

Page: 480

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Soft Computing has emerged as an important approach towards achieving intelligent computational paradigms where key elements are learning from experience in the presence of uncertainties, fuzzy belief functioos, and ·evolutioo of the computing strategies of the learning agent itself. Fuzzy, neural and evolutionary computing are the three major themes of soft computing. The book presents original research papers dealing with the theory of soft computing and its applicatioos in engineering design and manufacturing. The methodologies have been applied to a large variety of real life problems. Applicatioo of soft computing has provided the opportunity to integrate human like 'vagueness' and real life 'uncertainty' to an otherwise 'hard' computer programme. Now, a computer programme can learn, adapt, and evolve using soft computing. The book identifies the strengths and Iimitatioos of soft cOOlputing techniques, particularly with reference to their engineering applications. The applications range fran design optimisatioo to scheduling and image analysis. Goal optimisatioo with incomplete infmnatioo and under uncertainty is the key to solving real-life problems in design and manufacturing. Soft computing techniques presented in this book address these issues. Computatiooal complexity and efficient implementatioo of these techniques are also major concerns for realising useful industrial applications of soft computing. The different parts in the book also address these issues. The book cootains 9 parts, 8 of which are based 00 papers fran the '2nd On-line World Conference 00 Soft Computing in Engineering Design and Manufacture (WSC2),.

Genetic algorithms in multiobjective optimization problems : An application to polymer extrusion . In Proceedings of the Workshop on Multi ... Optimization for Engineering Design : Algorithms and Examples . New Delhi : Prentice - Hall .

Author: Kalyanmoy Deb

Publisher: John Wiley & Sons

ISBN: 047187339X

Category: Mathematics

Page: 540

View: 950

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Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. Comprehensive coverage of this growing area of research Carefully introduces each algorithm with examples and in-depth discussion Includes many applications to real-world problems, including engineering design and scheduling Includes discussion of advanced topics and future research Can be used as a course text or for self-study Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.