Genetic Algorithms In Engineering And Computer Science

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Genetic Algorithms in Engineering and Computer Science

Author : G. Winter
Publisher :
ISBN 13 :
Total Pages : 486 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Genetic Algorithms in Engineering and Computer Science by : G. Winter

Download or read book Genetic Algorithms in Engineering and Computer Science written by G. Winter and published by . This book was released on 1995 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Algorithms in Engineering and Computer Science Edited by G. Winter University of Las Palmas, Canary Islands, Spain J. Périaux Dassault Aviation, Saint Cloud, France M. Galán P. Cuesta University of Las Palmas, Canary Islands, Spain This attractive book alerts us to the existence of evolution based software — Genetic Algorithms and Evolution Strategies—used for the study of complex systems and difficult optimization problems unresolved until now. Evolution algorithms are artificial intelligence techniques which mimic nature according to the "survival of the fittest" (Darwin’s principle). They randomly encode physical (quantitative or qualitative) variables via digital DNA inside computers and are known for their robustness to better explore large search spaces and find near-global optima than traditional optimization methods. The objectives of this volume are two-fold: to present a compendium of state-of-the-art lectures delivered by recognized experts in the field on theoretical, numerical and applied aspects of Genetic Algorithms for the computational treatment of continuous, discrete and combinatorial optimization problems. to provide a bridge between Artificial Intelligence and Scientific Computing in order to increase the performance of evolution programs for solving real life problems. Fluid dynamics, structure mechanics, electromagnetics, automation control, resource optimization, image processing and economics are the featured multi-disciplinary areas among others in Engineering and Applied Sciences where evolution works impressively well. This volume is aimed at graduate students, applied mathematicians, computer scientists, researchers and engineers who face challenging design optimization problems in Industry. They will enjoy implementing new programs using these evolution techniques which have been experimented with by Nature for 3.5 billion years.

An Introduction to Genetic Algorithms

Author : Melanie Mitchell
Publisher : MIT Press
ISBN 13 : 9780262631853
Total Pages : 226 pages
Book Rating : 4.6/5 (318 download)

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Book Synopsis An Introduction to Genetic Algorithms by : Melanie Mitchell

Download or read book An Introduction to Genetic Algorithms written by Melanie Mitchell and published by MIT Press. This book was released on 1998-03-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

Genetic Algorithms and Engineering Design

Author : Mitsuo Gen
Publisher : John Wiley & Sons
ISBN 13 : 9780471127413
Total Pages : 436 pages
Book Rating : 4.1/5 (274 download)

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Book Synopsis Genetic Algorithms and Engineering Design by : Mitsuo Gen

Download or read book Genetic Algorithms and Engineering Design written by Mitsuo Gen and published by John Wiley & Sons. This book was released on 1997-01-21 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Genetic Algorithms and Evolution Strategy in Engineering and Computer Science

Author : D. Quagliarella
Publisher :
ISBN 13 :
Total Pages : 416 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Genetic Algorithms and Evolution Strategy in Engineering and Computer Science by : D. Quagliarella

Download or read book Genetic Algorithms and Evolution Strategy in Engineering and Computer Science written by D. Quagliarella and published by . This book was released on 1998-01-21 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of state-of-the-art lectures by experts in the field of theoretical, numerical and applied aspects of genetic algorithms for the computational treatment of continuous, discrete and combinatorial optimization problems. The theory presented in this book has numerous applications in fluid dynamics, structure mechanics, electromagnetic, automation control, resource optimization, image processing and economics

Genetic Algorithms and Fuzzy Multiobjective Optimization

Author : Masatoshi Sakawa
Publisher : Springer Science & Business Media
ISBN 13 : 9780792374527
Total Pages : 306 pages
Book Rating : 4.3/5 (745 download)

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Book Synopsis Genetic Algorithms and Fuzzy Multiobjective Optimization by : Masatoshi Sakawa

Download or read book Genetic Algorithms and Fuzzy Multiobjective Optimization written by Masatoshi Sakawa and published by Springer Science & Business Media. This book was released on 2002 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a wide range of actual real world applications. The theoretical material and applications place special stress on interactive decision-making aspects of fuzzy multiobjective optimization for human-centered systems in most realistic situations when dealing with fuzziness. The intended readers of this book are senior undergraduate students, graduate students, researchers, and practitioners in the fields of operations research, computer science, industrial engineering, management science, systems engineering, and other engineering disciplines that deal with the subjects of multiobjective programming for discrete or other hard optimization problems under fuzziness. Real world research applications are used throughout the book to illustrate the presentation. These applications are drawn from complex problems. Examples include flexible scheduling in a machine center, operation planning of district heating and cooling plants, and coal purchase planning in an actual electric power plant.

Evolutionary Algorithms in Engineering Applications

Author : Dipankar Dasgupta
Publisher : Springer Science & Business Media
ISBN 13 : 3662034239
Total Pages : 561 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Evolutionary Algorithms in Engineering Applications by : Dipankar Dasgupta

Download or read book Evolutionary Algorithms in Engineering Applications written by Dipankar Dasgupta and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Genetic Algorithms

Author : S.N. Sivanandam
Publisher : Springer Science & Business Media
ISBN 13 : 3540731903
Total Pages : 442 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Introduction to Genetic Algorithms by : S.N. Sivanandam

Download or read book Introduction to Genetic Algorithms written by S.N. Sivanandam and published by Springer Science & Business Media. This book was released on 2007-10-24 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.

Cellular Genetic Algorithms

Author : Enrique Alba
Publisher : Springer Science & Business Media
ISBN 13 : 0387776109
Total Pages : 251 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Cellular Genetic Algorithms by : Enrique Alba

Download or read book Cellular Genetic Algorithms written by Enrique Alba and published by Springer Science & Business Media. This book was released on 2009-04-05 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cellular Genetic Algorithms defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book with equal and parallel emphasis on both theory and practice. This book is a key source for studying and designing cellular GAs, as well as a self-contained primary reference book for these algorithms.

Genetic Algorithms in Search, Optimization, and Machine Learning

Author : David Edward Goldberg
Publisher : Addison-Wesley Professional
ISBN 13 :
Total Pages : 436 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Genetic Algorithms in Search, Optimization, and Machine Learning by : David Edward Goldberg

Download or read book Genetic Algorithms in Search, Optimization, and Machine Learning written by David Edward Goldberg and published by Addison-Wesley Professional. This book was released on 1989 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applications of genetic algorithms. Advanced operators and techniques in genetic search. Introduction to genetics-based machine learning. Applications of genetics-based machine learning. A look back, a glance ahead. A review of combinatorics and elementary probability. Pascal with random number generation for fortran, basic, and cobol programmers. A simple genetic algorithm (SGA) in pascal. A simple classifier system(SCS) in pascal. Partition coefficient transforms for problem-coding analysis.

Genetic Algorithms + Data Structures = Evolution Programs

Author : Zbigniew Michalewicz
Publisher : Springer Science & Business Media
ISBN 13 : 3662033151
Total Pages : 392 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Genetic Algorithms + Data Structures = Evolution Programs by : Zbigniew Michalewicz

Genetic Algorithms and Engineering Optimization

Author : Mitsuo Gen
Publisher : John Wiley & Sons
ISBN 13 : 9780471315315
Total Pages : 520 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Genetic Algorithms and Engineering Optimization by : Mitsuo Gen

Download or read book Genetic Algorithms and Engineering Optimization written by Mitsuo Gen and published by John Wiley & Sons. This book was released on 1999-12-28 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques

Author : Chis, Monica
Publisher : IGI Global
ISBN 13 : 1615208100
Total Pages : 282 pages
Book Rating : 4.6/5 (152 download)

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Book Synopsis Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques by : Chis, Monica

Download or read book Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques written by Chis, Monica and published by IGI Global. This book was released on 2010-06-30 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques lays the foundation for the successful integration of evolutionary computation into software engineering. It surveys techniques ranging from genetic algorithms, to swarm optimization theory, to ant colony optimization, demonstrating their uses and capabilities. These techniques are applied to aspects of software engineering such as software testing, quality assessment, reliability assessment, and fault prediction models, among others, to providing researchers, scholars and students with the knowledge needed to expand this burgeoning application.

Genetic Algorithms

Author : Julia Carson
Publisher :
ISBN 13 : 9781536118568
Total Pages : 0 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Genetic Algorithms by : Julia Carson

Download or read book Genetic Algorithms written by Julia Carson and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Chapter One, a revision and complementary analysis of three interesting cases where stochastic strategies are applied to get the optimal design of intensified schemes is presented. The revisited cases include multicomponent, extractive and reactive thermally coupled distillation. Chapter Two performs parameter optimisation on a genetic algorithm to skip the tuning parameter process during unmanned aerial vehicle path planning. Results show that truncation selection at 20% is highly recommended for genetic algorithm path planning application because of its low average path and computational costs. Chapter 3 describes the calibration of the numerical model of the Monte da Virgem telecommunications tower, located near the city of Porto, Portugal. The calibration of the numerical model of the tower relies on the application of an iterative method based on a genetic algorithm. Chapter 4 describes the genetic algorithm-based calibration procedure for a microscopic traffic simulation model, focusing on freeways and modern roundabouts. For both case studies, the genetic algorithm tool in MATLAB® was applied in order to reach the convergence between the outputs from Aimsun microscopic simulator and the observed data.

An Introduction to Genetic Algorithms for Scientists and Engineers

Author : David A. Coley
Publisher : World Scientific
ISBN 13 : 9789810236021
Total Pages : 248 pages
Book Rating : 4.2/5 (36 download)

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Book Synopsis An Introduction to Genetic Algorithms for Scientists and Engineers by : David A. Coley

Download or read book An Introduction to Genetic Algorithms for Scientists and Engineers written by David A. Coley and published by World Scientific. This book was released on 1999 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This invaluable book has been designed to be useful to most practising scientists and engineers, whatever their field and however rusty their mathematics and programming might be. The approach taken is largely practical, with algorithms being presented in full and working code (in BASIC, FORTRAN, PASCAL AND C) included on a floppy disk to help the reader get up and running as quickly as possible. The text could also be used as part of an undergraduate course on search and optimisation. Student exercises are included at the end of several of the chapters, many of which are computer-based and designed to encourage exploration of the method.

Genetic Algorithms in Electromagnetics

Author : Randy L. Haupt
Publisher : John Wiley & Sons
ISBN 13 : 0470106271
Total Pages : 317 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Genetic Algorithms in Electromagnetics by : Randy L. Haupt

Download or read book Genetic Algorithms in Electromagnetics written by Randy L. Haupt and published by John Wiley & Sons. This book was released on 2007-04-27 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thorough and insightful introduction to using genetic algorithms to optimize electromagnetic systems Genetic Algorithms in Electromagnetics focuses on optimizing the objective function when a computer algorithm, analytical model, or experimental result describes the performance of an electromagnetic system. It offers expert guidance to optimizing electromagnetic systems using genetic algorithms (GA), which have proven to be tenacious in finding optimal results where traditional techniques fail. Genetic Algorithms in Electromagnetics begins with an introduction to optimization and several commonly used numerical optimization routines, and goes on to feature: Introductions to GA in both binary and continuous variable forms, complete with examples of MATLAB(r) commands Two step-by-step examples of optimizing antenna arrays as well as a comprehensive overview of applications of GA to antenna array design problems Coverage of GA as an adaptive algorithm, including adaptive and smart arrays as well as adaptive reflectors and crossed dipoles Explanations of the optimization of several different wire antennas, starting with the famous "crooked monopole" How to optimize horn, reflector, and microstrip patch antennas, which require significantly more computing power than wire antennas Coverage of GA optimization of scattering, including scattering from frequency selective surfaces and electromagnetic band gap materials Ideas on operator and parameter selection for a GA Detailed explanations of particle swarm optimization and multiple objective optimization An appendix of MATLAB code for experimentation

Genetic Algorithms + Data Structures = Evolution Programs

Author : Zbigniew Michalewicz
Publisher : Springer Science & Business Media
ISBN 13 : 3662028301
Total Pages : 257 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Genetic Algorithms + Data Structures = Evolution Programs by : Zbigniew Michalewicz

Download or read book Genetic Algorithms + Data Structures = Evolution Programs written by Zbigniew Michalewicz and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'What does your Master teach?' asked a visitor. 'Nothing,' said the disciple. 'Then why does he give discourses?' 'He only points the way - he teaches nothing.' Anthony de Mello, One Minute Wisdom During the last three decades there has been a growing interest in algorithms which rely on analogies to natural processes. The emergence of massively par allel computers made these algorithms of practical interest. The best known algorithms in this class include evolutionary programming, genetic algorithms, evolution strategies, simulated annealing, classifier systems, and neural net works. Recently (1-3 October 1990) the University of Dortmund, Germany, hosted the First Workshop on Parallel Problem Solving from Nature [164]. This book discusses a subclass of these algorithms - those which are based on the principle of evolution (survival of the fittest). In such algorithms a popu lation of individuals (potential solutions) undergoes a sequence of unary (muta tion type) and higher order (crossover type) transformations. These individuals strive for survival: a selection scheme, biased towards fitter individuals, selects the next generation. After some number of generations, the program converges - the best individual hopefully represents the optimum solution. There are many different algorithms in this category. To underline the sim ilarities between them we use the common term "evolution programs" .

Network Models and Optimization

Author : Mitsuo Gen
Publisher : Springer Science & Business Media
ISBN 13 : 1848001819
Total Pages : 692 pages
Book Rating : 4.8/5 (48 download)

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Book Synopsis Network Models and Optimization by : Mitsuo Gen

Download or read book Network Models and Optimization written by Mitsuo Gen and published by Springer Science & Business Media. This book was released on 2008-07-10 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.