Evolutionary Algorithms In Engineering Applications

Author: Dipankar Dasgupta
Publisher: Springer Science & Business Media
ISBN: 3662034239
Size: 77.60 MB
Format: PDF, Mobi
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Evolutionary Algorithms In Engineering Applications from the Author: Dipankar Dasgupta. 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.

Genetic Algorithms In Engineering Systems

Author: Ali M. S. Zalzala
Publisher: IET
ISBN: 9780852969021
Size: 49.57 MB
Format: PDF, ePub, Mobi
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Genetic Algorithms In Engineering Systems from the Author: Ali M. S. Zalzala. Arising out of the highly successful 1st IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA '95), held at the University of Sheffield UK, this book comprises commissioned papers from some of the highest quality contributions to the conference. Chosen for their experience in the field, the authorship is international and drawn from academia and industry. 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.

Applications Of Multi Objective Evolutionary Algorithms

Author: Carlos A. Coello Coello
Publisher: World Scientific
ISBN: 9812561064
Size: 23.22 MB
Format: PDF
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Applications Of Multi Objective Evolutionary Algorithms from the Author: Carlos A. Coello Coello. - Detailed MOEA applications discussed by international experts - State-of-the-art practical insights in tackling statistical optimization with MOEAs - A unique monograph covering a wide spectrum of real-world applications - Step-by-step discussion of MOEA applications in a variety of domains

Introduction To Evolutionary Algorithms

Author: Xinjie Yu
Publisher: Springer Science & Business Media
ISBN: 9781849961295
Size: 56.96 MB
Format: PDF, Docs
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Introduction To Evolutionary Algorithms from the Author: Xinjie Yu. Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. It covers such hot topics as: • genetic algorithms, • differential evolution, • swarm intelligence, and • artificial immune systems. The reader is introduced to a range of applications, as Introduction to Evolutionary Algorithms demonstrates how to model real world problems, how to encode and decode individuals, and how to design effective search operators according to the chromosome structures with examples of constraint optimization, multiobjective optimization, combinatorial optimization, and supervised/unsupervised learning. This emphasis on practical applications will benefit all students, whether they choose to continue their academic career or to enter a particular industry. Introduction to Evolutionary Algorithms is intended as a textbook or self-study material for both advanced undergraduates and graduate students. Additional features such as recommended further reading and ideas for research projects combine to form an accessible and interesting pedagogical approach to this widely used discipline.

Artificial Intelligence And Evolutionary Algorithms In Engineering Systems

Author: L Padma Suresh
Publisher: Springer
ISBN: 8132221354
Size: 62.76 MB
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Artificial Intelligence And Evolutionary Algorithms In Engineering Systems from the Author: L Padma Suresh. The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

Evolutionary Computation And Optimization Algorithms In Software Engineering Applications And Techniques

Author: Chis, Monica
Publisher: IGI Global
ISBN: 1615208100
Size: 58.72 MB
Format: PDF, ePub, Docs
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Evolutionary Computation And Optimization Algorithms In Software Engineering Applications And Techniques from the Author: Chis, Monica. 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 In Engineering And Computer Science

Author: G. Winter
Publisher: John Wiley & Sons
ISBN:
Size: 17.28 MB
Format: PDF, ePub
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Genetic Algorithms In Engineering And Computer Science from the Author: G. Winter. 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.

Genetic Algorithms And Evolution Strategy In Engineering And Computer Science

Author: D. Quagliarella
Publisher: John Wiley & Son Ltd
ISBN: 9780471977100
Size: 43.20 MB
Format: PDF, ePub
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Genetic Algorithms And Evolution Strategy In Engineering And Computer Science from the Author: D. Quagliarella. 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 Engineering Design

Author: Mitsuo Gen
Publisher: John Wiley & Sons
ISBN: 9780471127413
Size: 16.63 MB
Format: PDF, Kindle
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Genetic Algorithms And Engineering Design from the Author: Mitsuo Gen. The last few years have seen important advances in the use of genetic algorithms to address challenging optimization problems in industrial engineering. 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 engineering and operations research. Beginning with a tutorial on genetic algorithm fundamentals and their use in solving constrained and combinatorial optimization problems, the book applies these techniques to problems in specific areas—sequencing, scheduling and production plans, transportation and vehicle routing, facility layout, location-allocation, and more. Each topic features a clearly written problem description, mathematical model, and summary of conventional heuristic algorithms. All algorithms are explained in intuitive, rather than highly-technical, language and are reinforced with illustrative figures and numerical examples. Written by two internationally acknowledged experts in the field, Genetic Algorithms and Engineering Design features original material on the foundation and application of genetic algorithms, and also standardizes the terms and symbols used in other sources—making this complex subject truly accessible to the beginner as well as to the more advanced reader. Ideal for both self-study and classroom use, this self-contained reference provides indispensable state-of-the-art guidance to professionals and students working in industrial engineering, management science, operations research, computer science, and artificial intelligence.