Genetic and Evolutionary Computing

This book gathers papers presented at the 13th International Conference on Genetic and Evolutionary Computing (ICGEC 2019), which was held in Qingdao, China, from 1st to 3rd, November 2019.

Genetic and Evolutionary Computing

Author: Jeng-Shyang Pan

Publisher: Springer Nature

ISBN: 9811533083

Page: 589

View: 688

This book gathers papers presented at the 13th International Conference on Genetic and Evolutionary Computing (ICGEC 2019), which was held in Qingdao, China, from 1st to 3rd, November 2019. Since it was established, in 2006, the ICGEC conference series has been devoted to new approaches with a focus on evolutionary computing. Today, it is a forum for the researchers and professionals in all areas of computational intelligence including evolutionary computing, machine learning, soft computing, data mining, multimedia and signal processing, swarm intelligence and security. The book appeals to policymakers, academics, educators, researchers in pedagogy and learning theory, school teachers, and other professionals in the learning industry, and further and continuing education.

Genetic and Evolutionary Computing

This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at ICGEC 2015, the 9th International Conference on Genetic and Evolutionary Computing.

Genetic and Evolutionary Computing

Author: Thi Thi Zin

Publisher: Springer

ISBN: 3319232045

Page: 466

View: 787

This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at ICGEC 2015, the 9th International Conference on Genetic and Evolutionary Computing. The conference this year was technically co-sponsored by Ministry of Science and Technology, Myanmar, University of Computer Studies, Yangon, University of Miyazaki in Japan, Kaohsiung University of Applied Science in Taiwan, Fujian University of Technology in China and VSB-Technical University of Ostrava. ICGEC 2015 is held from 26-28, August, 2015 in Yangon, Myanmar. Yangon, the most multiethnic and cosmopolitan city in Myanmar, is the main gateway to the country. Despite being the commercial capital of Myanmar, Yangon is a city engulfed by its rich history and culture, an integration of ancient traditions and spiritual heritage. The stunning SHWEDAGON Pagoda is the center piece of Yangon city, which itself is famous for the best British colonial era architecture. Of particular interest in many shops of Bogyoke Aung San Market, and of world renown, are Myanmar’s precious stones-rubies, sapphires and jade. At night time, Chinatown comes alive with its pungent aromas and delicious street food. The conference is intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing.

Genetic and Evolutionary Computation

By explaining the basic introductory theory, typical application areas and detailed implementation in one coherent volume, this book will appeal to a wide audience from software developers to medical scientists.

Genetic and Evolutionary Computation

Author: Stephen L. Smith

Publisher: John Wiley & Sons

ISBN: 1119956781

Page: 250

View: 658

Genetic and Evolutionary Computation: Medical Applications provides an overview of the range of GEC techniques being applied to medicine and healthcare in a context that is relevant not only for existing GEC practitioners but also those from other disciplines, particularly health professionals. There is rapidly increasing interest in applying evolutionary computation to problems in medicine, but to date no text that introduces evolutionary computation in a medical context. By explaining the basic introductory theory, typical application areas and detailed implementation in one coherent volume, this book will appeal to a wide audience from software developers to medical scientists. Centred around a set of nine case studies on the application of GEC to different areas of medicine, the book offers an overview of applications of GEC to medicine, describes applications in which GEC is used to analyse medical images and data sets, derive advanced models, and suggest diagnoses and treatments, finally providing hints about possible future advancements of genetic and evolutionary computation in medicine. Explores the rapidly growing area of genetic and evolutionary computation in context of its viable and exciting payoffs in the field of medical applications. Explains the underlying theory, typical applications and detailed implementation. Includes general sections about the applications of GEC to medicine and their expected future developments, as well as specific sections on applications of GEC to medical imaging, analysis of medical data sets, advanced modelling, diagnosis and treatment. Features a wide range of tables, illustrations diagrams and photographs.

Introduction to Evolutionary Computing

The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Introduction to Evolutionary Computing

Author: A.E. Eiben

Publisher: Springer Science & Business Media

ISBN: 9783540401841

Page: 300

View: 717

The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Genetic and Evolutionary Computation GECCO 2003

The set LNCS 2723 and LNCS 2724 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2003, held in Chicago, IL, USA in July 2003.

Genetic and Evolutionary Computation     GECCO 2003

Author: Erick Cantú-Paz

Publisher: Springer

ISBN: 3540451102

Page: 1280

View: 280

The set LNCS 2723 and LNCS 2724 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2003, held in Chicago, IL, USA in July 2003. The 193 revised full papers and 93 poster papers presented were carefully reviewed and selected from a total of 417 submissions. The papers are organized in topical sections on a-life adaptive behavior, agents, and ant colony optimization; artificial immune systems; coevolution; DNA, molecular, and quantum computing; evolvable hardware; evolutionary robotics; evolution strategies and evolutionary programming; evolutionary sheduling routing; genetic algorithms; genetic programming; learning classifier systems; real-world applications; and search based software engineering.

Advances in Evolutionary Computing

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.

Advances in Evolutionary Computing

Author: Ashish Ghosh

Publisher: Springer Science & Business Media

ISBN: 3642189652

Page: 1006

View: 309

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.

Introduction to Evolutionary Algorithms

Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms.

Introduction to Evolutionary Algorithms

Author: Xinjie Yu

Publisher: Springer Science & Business Media

ISBN: 9781849961295

Page: 422

View: 182

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.

Representations for Genetic and Evolutionary Algorithms

This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance.

Representations for Genetic and Evolutionary Algorithms

Author: Franz Rothlauf

Publisher: Springer Science & Business Media

ISBN: 9783540324447

Page: 325

View: 222

In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations.

Evolutionary Computation

Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving.

Evolutionary Computation

Author: D. Dumitrescu

Publisher: CRC Press

ISBN: 9780849305887

Page: 424

View: 607

Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation. Evolutionary Computation presents the basic principles of evolutionary computing: genetic algorithms, evolution strategies, evolutionary programming, genetic programming, learning classifier systems, population models, and applications. It includes detailed coverage of binary and real encoding, including selection, crossover, and mutation, and discusses the (m+l) and (m,l) evolution strategy principles. The focus then shifts to applications: decision strategy selection, training and design of neural networks, several approaches to pattern recognition, cellular automata, applications of genetic programming, and more.

Evolutionary Computation for Modeling and Optimization

This book presents a large number of homework problems, projects, and experiments, with a goal of illustrating single aspects of evolutionary computation and comparing different methods.

Evolutionary Computation for Modeling and Optimization

Author: Daniel Ashlock

Publisher: Springer Science & Business Media

ISBN: 9780387319094

Page: 572

View: 733

Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.

Evolutionary Computation 1

This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming.

Evolutionary Computation 1

Author: Thomas Baeck

Publisher: CRC Press

ISBN: 1351989421

Page: 378

View: 110

The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.

Parameter Setting in Evolutionary Algorithms

Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves.

Parameter Setting in Evolutionary Algorithms

Author: F.J. Lobo

Publisher: Springer Science & Business Media

ISBN: 3540694315

Page: 318

View: 106

One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.

Genetic and Evolutionary Computation GECCO 2004

The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004.

Genetic and Evolutionary Computation     GECCO 2004

Author: Kalyanmoy Deb

Publisher: Springer Science & Business Media

ISBN: 3540223444

Page: 1448

View: 709

The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004. The 230 revised full papers and 104 poster papers presented were carefully reviewed and selected from 460 submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; artificial immune systems, biological applications; coevolution; evolutionary robotics; evolution strategies and evolutionary programming; evolvable hardware; genetic algorithms; genetic programming; learning classifier systems; real world applications; and search-based software engineering.

An Introduction to Genetic Algorithms

Genetic algorithms : an overview - Genetic algorithms in problem solving - Genetic algorithms in scientific models - Theoretical foundations of genetic algorithms - Implementing a genetic algorithm.

An Introduction to Genetic Algorithms

Author: Melanie Mitchell

Publisher: MIT Press

ISBN: 9780262631853

Page: 209

View: 904

Genetic algorithms : an overview - Genetic algorithms in problem solving - Genetic algorithms in scientific models - Theoretical foundations of genetic algorithms - Implementing a genetic algorithm.