Evolutionary Algorithms In Engineering Applications

Author: Dipankar Dasgupta
Publisher: Springer Science & Business Media
ISBN: 3662034239
Size: 67.58 MB
Format: PDF
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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: 69.12 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.

Genetic Algorithms And Engineering Design

Author: Mitsuo Gen
Publisher: John Wiley & Sons
ISBN: 9780471127413
Size: 21.47 MB
Format: PDF, ePub
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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.

Genetic Algorithms And Evolution Strategy In Engineering And Computer Science

Author: D. Quagliarella
Publisher: John Wiley & Son Ltd
ISBN: 9780471977100
Size: 71.71 MB
Format: PDF, Docs
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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

Meta Heuristic And Evolutionary Algorithms For Engineering Optimization

Author: Omid Bozorg-Haddad
Publisher: John Wiley & Sons
ISBN: 1119387078
Size: 11.77 MB
Format: PDF, Kindle
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Meta Heuristic And Evolutionary Algorithms For Engineering Optimization from the Author: Omid Bozorg-Haddad. A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.

Applications Of Multi Objective Evolutionary Algorithms

Author: Carlos A. Coello Coello
Publisher: World Scientific
ISBN: 9812561064
Size: 73.33 MB
Format: PDF, ePub, Docs
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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

Artificial Intelligence And Evolutionary Algorithms In Engineering Systems

Author: L Padma Suresh
Publisher: Springer
ISBN: 8132221354
Size: 27.47 MB
Format: PDF
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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.

Genetic Algorithms In Engineering And Computer Science

Author: G. Winter
Publisher: John Wiley & Sons
ISBN:
Size: 29.90 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. PĂ©riaux Dassault Aviation, Saint Cloud, France M. GalĂĄn 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.

Evolutionary Algorithms And Intelligent Tools In Engineering Optimization

Author: William Annicchiarico
Publisher: Wit Pr/Computational Mechanics
ISBN: 9781845640385
Size: 20.85 MB
Format: PDF, ePub
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Evolutionary Algorithms And Intelligent Tools In Engineering Optimization from the Author: William Annicchiarico. Evolutionary Algorithms are very powerful techniques used to find solutions to real-world search and optimization problems. They are artificial intelligence techniques which mimic nature according to Darwin's principal of the "survival of the fittest" in order to explore and explode large search space and find near-global optima. In this book, a large spectrum of innovative evolutionary and intelligence methods are presented and used for solving various application problems, name and among others: Genetic Algorithms, Evolutions Strategies or Constrained Optimization, Genetic Programming, Sampling Methods in Evolutionary Computation, Tabu Methods, Metamodelassisted Evolutionary Algorithms, Multi Objective Robust Design, Hierarchical Asynchronous Parallel Evolutionary Algorithms, Micro Distributed Genetic Algorithms and Hybrid Optimization. The reader will easily access the comprehensive methods described in the fourteen chapters that work impressively well on practical problems representative of real engineering situations in the areas of Control, Electronics, Civil Engineering, Aerospace Engineering, Turbomachinery and Medical Engineering and Energy. This collective book, written by internationally recognized experts in the fields of evolutionary design optimization, will therefore be of significant interest and value to computer scientists, researchers and post graduate students, and practicing senior or young engineers involved in complex design Optimization problems.