Variants of Evolutionary Algorithms for Real-World Applications

Variants of Evolutionary Algorithms for Real-World Applications

Author: Raymond Chiong

Publisher: Springer Science & Business Media

Published: 2011-11-13

Total Pages: 470

ISBN-13: 3642234240

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Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book “Variants of Evolutionary Algorithms for Real-World Applications” aims to promote the practitioner’s view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter re-visiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the prediction of soil properties, automated tissue classification for MRI images, and database query optimisation, among others. These chapters demonstrate how different types of problems can be successfully solved using variants of EAs and how the solution approaches are constructed, in a way that can be understood and reproduced with little prior knowledge on optimisation.


Book Synopsis Variants of Evolutionary Algorithms for Real-World Applications by : Raymond Chiong

Download or read book Variants of Evolutionary Algorithms for Real-World Applications written by Raymond Chiong and published by Springer Science & Business Media. This book was released on 2011-11-13 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book “Variants of Evolutionary Algorithms for Real-World Applications” aims to promote the practitioner’s view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter re-visiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the prediction of soil properties, automated tissue classification for MRI images, and database query optimisation, among others. These chapters demonstrate how different types of problems can be successfully solved using variants of EAs and how the solution approaches are constructed, in a way that can be understood and reproduced with little prior knowledge on optimisation.

Applications of Evolutionary Computation

Applications of Evolutionary Computation

Author: Paul Kaufmann (Computer scientist)

Publisher:

Published: 2019

Total Pages: 642

ISBN-13: 9783030166939

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This book constitutes the refereed proceedings of the 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoMUSART. The 44 revised full papers presented were carefully reviewed and selected from 66 submissions. They were organized in topical sections named: Engineering and Real World Applications; Games; General; Image and Signal Processing; Life Sciences; Networks and Distributed Systems; Neuroevolution and Data Analytics; Numerical Optimization: Theory, Benchmarks, and Applications; Robotics. --


Book Synopsis Applications of Evolutionary Computation by : Paul Kaufmann (Computer scientist)

Download or read book Applications of Evolutionary Computation written by Paul Kaufmann (Computer scientist) and published by . This book was released on 2019 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoMUSART. The 44 revised full papers presented were carefully reviewed and selected from 66 submissions. They were organized in topical sections named: Engineering and Real World Applications; Games; General; Image and Signal Processing; Life Sciences; Networks and Distributed Systems; Neuroevolution and Data Analytics; Numerical Optimization: Theory, Benchmarks, and Applications; Robotics. --

Advances in Evolutionary Computing

Advances in Evolutionary Computing

Author: Ashish Ghosh

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 1001

ISBN-13: 3642189652

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This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.


Book Synopsis Advances in Evolutionary Computing by : Ashish Ghosh

Download or read book Advances in Evolutionary Computing written by Ashish Ghosh and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.

Applications of Multi-objective Evolutionary Algorithms

Applications of Multi-objective Evolutionary Algorithms

Author: Carlos A. Coello Coello

Publisher: World Scientific

Published: 2004

Total Pages: 792

ISBN-13: 9812561064

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- 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


Book Synopsis Applications of Multi-objective Evolutionary Algorithms by : Carlos A. Coello Coello

Download or read book Applications of Multi-objective Evolutionary Algorithms written by Carlos A. Coello Coello and published by World Scientific. This book was released on 2004 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: - 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

Industrial Applications of Evolutionary Algorithms

Industrial Applications of Evolutionary Algorithms

Author: Ernesto Sanchez

Publisher: Springer Science & Business Media

Published: 2012-01-28

Total Pages: 137

ISBN-13: 3642274676

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"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.


Book Synopsis Industrial Applications of Evolutionary Algorithms by : Ernesto Sanchez

Download or read book Industrial Applications of Evolutionary Algorithms written by Ernesto Sanchez and published by Springer Science & Business Media. This book was released on 2012-01-28 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Real-World Applications of Genetic Algorithms

Real-World Applications of Genetic Algorithms

Author: Olympia Roeva

Publisher: BoD – Books on Demand

Published: 2012-03-07

Total Pages: 379

ISBN-13: 9535101463

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The book addresses some of the most recent issues, with the theoretical and methodological aspects, of evolutionary multi-objective optimization problems and the various design challenges using different hybrid intelligent approaches. Multi-objective optimization has been available for about two decades, and its application in real-world problems is continuously increasing. Furthermore, many applications function more effectively using a hybrid systems approach. The book presents hybrid techniques based on Artificial Neural Network, Fuzzy Sets, Automata Theory, other metaheuristic or classical algorithms, etc. The book examines various examples of algorithms in different real-world application domains as graph growing problem, speech synthesis, traveling salesman problem, scheduling problems, antenna design, genes design, modeling of chemical and biochemical processes etc.


Book Synopsis Real-World Applications of Genetic Algorithms by : Olympia Roeva

Download or read book Real-World Applications of Genetic Algorithms written by Olympia Roeva and published by BoD – Books on Demand. This book was released on 2012-03-07 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book addresses some of the most recent issues, with the theoretical and methodological aspects, of evolutionary multi-objective optimization problems and the various design challenges using different hybrid intelligent approaches. Multi-objective optimization has been available for about two decades, and its application in real-world problems is continuously increasing. Furthermore, many applications function more effectively using a hybrid systems approach. The book presents hybrid techniques based on Artificial Neural Network, Fuzzy Sets, Automata Theory, other metaheuristic or classical algorithms, etc. The book examines various examples of algorithms in different real-world application domains as graph growing problem, speech synthesis, traveling salesman problem, scheduling problems, antenna design, genes design, modeling of chemical and biochemical processes etc.

Evolutionary Computation

Evolutionary Computation

Author: Ashish M. Gujarathi

Publisher: CRC Press

Published: 2016-12-01

Total Pages: 652

ISBN-13: 1315342162

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Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications. Covering both the theory and applications of evolutionary computation, the book offers exhaustive coverage of several topics on nontraditional evolutionary techniques, details working principles of new and popular evolutionary algorithms, and discusses case studies on both scientific and real-world applications of optimization


Book Synopsis Evolutionary Computation by : Ashish M. Gujarathi

Download or read book Evolutionary Computation written by Ashish M. Gujarathi and published by CRC Press. This book was released on 2016-12-01 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications. Covering both the theory and applications of evolutionary computation, the book offers exhaustive coverage of several topics on nontraditional evolutionary techniques, details working principles of new and popular evolutionary algorithms, and discusses case studies on both scientific and real-world applications of optimization

Evolutionary Algorithms and Neural Networks

Evolutionary Algorithms and Neural Networks

Author: Seyedali Mirjalili

Publisher: Springer

Published: 2018-06-26

Total Pages: 156

ISBN-13: 3319930257

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This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.


Book Synopsis Evolutionary Algorithms and Neural Networks by : Seyedali Mirjalili

Download or read book Evolutionary Algorithms and Neural Networks written by Seyedali Mirjalili and published by Springer. This book was released on 2018-06-26 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.

Introduction to Evolutionary Algorithms

Introduction to Evolutionary Algorithms

Author: Xinjie Yu

Publisher: Springer Science & Business Media

Published: 2010-06-10

Total Pages: 427

ISBN-13: 1849961298

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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.


Book Synopsis Introduction to Evolutionary Algorithms by : Xinjie Yu

Download or read book Introduction to Evolutionary Algorithms written by Xinjie Yu and published by Springer Science & Business Media. This book was released on 2010-06-10 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Real-World Applications of Evolutionary Computing

Real-World Applications of Evolutionary Computing

Author: Stefano Cagnoni

Publisher: Springer

Published: 2003-07-31

Total Pages: 400

ISBN-13: 9783540455615

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The increasingly active eld of Evolutionary Computation (EC) provides val- ble tools, inspired by the theory of natural selection and genetic inheritance, to problem solving, machine learning, and optimization in many real-world app- cations. Despite some early intuitions about EC, that can be dated back to the - vention of computers, and a better formal de nition of EC, made in the 1960s, the quest for real-world applications of EC only began in the late 1980s. The dramatic increase in computer performances in the last decade of the 20th c- tury gave rise to a positive feedback process: EC techniques became more and more applicable, stimulating the growth of interest in their study, and allowing, in turn, new powerful EC paradigms to be devised. In parallel with new theoretical results, the number of elds to which EC is being applied is increasing day by day, along with the complexity of applications and application domains. In particular, industrially relevant elds, such as signal and image processing, computer vision, pattern recognition, industrial control, telecommunication, scheduling and timetabling, and aerospace engineering are employing EC techniques to solve complex real-world problems.


Book Synopsis Real-World Applications of Evolutionary Computing by : Stefano Cagnoni

Download or read book Real-World Applications of Evolutionary Computing written by Stefano Cagnoni and published by Springer. This book was released on 2003-07-31 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasingly active eld of Evolutionary Computation (EC) provides val- ble tools, inspired by the theory of natural selection and genetic inheritance, to problem solving, machine learning, and optimization in many real-world app- cations. Despite some early intuitions about EC, that can be dated back to the - vention of computers, and a better formal de nition of EC, made in the 1960s, the quest for real-world applications of EC only began in the late 1980s. The dramatic increase in computer performances in the last decade of the 20th c- tury gave rise to a positive feedback process: EC techniques became more and more applicable, stimulating the growth of interest in their study, and allowing, in turn, new powerful EC paradigms to be devised. In parallel with new theoretical results, the number of elds to which EC is being applied is increasing day by day, along with the complexity of applications and application domains. In particular, industrially relevant elds, such as signal and image processing, computer vision, pattern recognition, industrial control, telecommunication, scheduling and timetabling, and aerospace engineering are employing EC techniques to solve complex real-world problems.