Industrial Applications Of Evolutionary Algorithms


Industrial Applications Of Evolutionary Algorithms
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Industrial Applications Of Genetic Algorithms


Industrial Applications Of Genetic Algorithms
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Author : Charles Karr
language : en
Publisher: CRC Press
Release Date : 1998-12-29

Industrial Applications Of Genetic Algorithms written by Charles Karr and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-12-29 with Computers categories.


Genetic algorithms (GAs) are computer-based search techniques patterned after the genetic mechanisms of biological organisms that have adapted and flourished in changing, highly competitive environments for millions of years. GAs have been successfully applied to problems in a variety of studies, and their popularity continues to increase because of their effectiveness, applicability, and ease of use. Industrial Applications of Genetic Algorithms shows how GAs have made the leap form their origins in the laboratory to the practicing engineer's toolbox. Each chapter in the book describes a project completed by a graduate student at the University of Alabama.



Industrial Applications Of Evolutionary Algorithms


Industrial Applications Of Evolutionary Algorithms
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Author : Ernesto Sanchez
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-28

Industrial Applications Of Evolutionary Algorithms written by Ernesto Sanchez and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-28 with Technology & Engineering categories.


"Industrial applications of evolutionary algorithms" is intended as a resource for both experienced users of evolutionary algorithms and researchers that are beginning to approach these fascinating optimization techniques. Experienced users will find interesting details of real-world problems, advice on solving issues related to fitness computation or modeling, and suggestions on how to set the appropriate parameters to reach optimal solutions. Beginners will find a thorough introduction to evolutionary computation, and a complete presentation of several classes of evolutionary algorithms exploited to solve different problems. Inside, scholars will find useful examples on how to fill the gap between purely theoretical examples and industrial problems. The collection of case studies presented is also extremely appealing for anyone interested in Evolutionary Computation, but without direct access to extensive technical literature on the subject. After the introduction, each chapter in the book presents a test case, and is organized so that it can be read independently from the rest: all the information needed to understand the problem and the approach is reported in each part. Chapters are grouped by three themes of particular interest for real-world applications, namely prototype-based validation, reliability and test generation. The authors hope that this volume will help to expose the flexibility and efficiency of evolutionary techniques, encouraging more companies to adopt them; and that, most of all, you will enjoy your reading.



Information Processing With Evolutionary Algorithms


Information Processing With Evolutionary Algorithms
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Author : Manuel Grana
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-30

Information Processing With Evolutionary Algorithms written by Manuel Grana and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-30 with Computers categories.


Provides a broad sample of current information processing applications Includes examples of successful applications that will encourage practitioners to apply the techniques described in the book to real-life problems



Soft Computing And Industry


Soft Computing And Industry
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Author : Rajkumar Roy
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Soft Computing And Industry written by Rajkumar Roy and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.


Soft computing embraces various methodologies for the development of intelligent systems that have been successfully applied to a large number of real-world problems. Soft Computing in Industry contains a collection of papers that were presented at the 6th On-line World Conference on Soft Computing in Industrial Applications that was held in September 2001. It provides a comprehensive overview of recent theoretical developments in soft computing as well as of successful industrial applications. It is divided into seven parts covering material on: keynote papers on various subjects ranging from computing with autopoietic systems to the effects of the Internet on education; intelligent control; classification, clustering and optimization; image and signal processing; agents, multimedia and Internet; theoretical advances; prediction, design and diagnosis. The book is aimed at researchers and professional engineers who develop and apply intelligent systems in computer engineering.



Dna Computing Based Genetic Algorithm


Dna Computing Based Genetic Algorithm
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Author : Jili Tao
language : en
Publisher: Springer Nature
Release Date : 2020-07-01

Dna Computing Based Genetic Algorithm written by Jili Tao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-01 with Computers categories.


This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier. It presents several DNA/RNA-based genetic algorithms and their modifications, which are tested using benchmarks, as well as detailed information on the implementation steps and program code. In addition to single-objective optimization, here genetic algorithms are also used to solve multi-objective optimization for neural network modeling, fuzzy control, model predictive control and PID control. In closing, new topics such as Q-learning and CNN are introduced. The book offers a valuable reference guide for researchers and designers in system modeling and control, and for senior undergraduate and graduate students at colleges and universities.



Fusion Of Neural Networks Fuzzy Systems And Genetic Algorithms


Fusion Of Neural Networks Fuzzy Systems And Genetic Algorithms
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Author : Lakhmi C. Jain
language : en
Publisher: CRC Press
Release Date : 2020-01-29

Fusion Of Neural Networks Fuzzy Systems And Genetic Algorithms written by Lakhmi C. Jain and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-29 with Computers categories.


Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include: direct frequency converters electro-hydraulic systems motor control toaster control speech recognition vehicle routing fault diagnosis Asynchronous Transfer Mode (ATM) communications networks telephones for hard-of-hearing people control of gas turbine aero-engines telecommunications systems design Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.



Applications Of Evolutionary Computing


Applications Of Evolutionary Computing
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Author : Anna I. Esparcia-Alcázar
language : en
Publisher: Springer
Release Date : 2013-03-12

Applications Of Evolutionary Computing written by Anna I. Esparcia-Alcázar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-12 with Computers categories.


This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoBIO, and EvoMUSART. The 65 revised full papers presented were carefully reviewed and selected from 119 submissions. EvoApplications 2013 consisted of the following 12 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary computation in robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).



Evolutionary Multiobjective Optimization


Evolutionary Multiobjective Optimization
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Author : Ajith Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-09-05

Evolutionary Multiobjective Optimization written by Ajith Abraham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-09-05 with Computers categories.


Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique.



Introduction To Evolutionary Algorithms


Introduction To Evolutionary Algorithms
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Author : Xinjie Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-10

Introduction To Evolutionary Algorithms written by Xinjie Yu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-10 with Computers categories.


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.



Evolutionary Computation In Scheduling


Evolutionary Computation In Scheduling
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Author : Amir H. Gandomi
language : en
Publisher: John Wiley & Sons
Release Date : 2020-05-19

Evolutionary Computation In Scheduling written by Amir H. Gandomi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-19 with Mathematics categories.


Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches. Evolutionary Computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book: Provides a representative sampling of real-world problems currently being tackled by practitioners Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence Consists of four main parts: Introduction to Scheduling Problems, Computational Issues in Scheduling Problems, Evolutionary Computation, and Evolutionary Computations for Scheduling Problems Evolutionary Computation in Scheduling is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering.