Homepage / Searching for: introduction to evolutionary algorithms

Welcome to Read Book Online

Download introduction to evolutionary algorithms or read introduction to evolutionary algorithms online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get introduction to evolutionary algorithms book now. Note:! If the content not Found, you must refresh this page manually.

Introduction To Evolutionary Algorithms

DOWNLOAD
Author by : Xinjie Yu
Languange Used : en
Release Date : 2010-06-10
Publisher by : Springer Science & Business Media

ISBN : 9781849961295

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....

Introduction To Evolutionary Computing

DOWNLOAD
Author by : Agoston E. Eiben
Languange Used : en
Release Date : 2013-03-14
Publisher by : Springer Science & Business Media

ISBN : 9783662050941

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....

An Introduction To Genetic Algorithms

DOWNLOAD
Author by : Melanie Mitchell
Languange Used : en
Release Date : 1998-03-02
Publisher by : MIT Press

ISBN : 0262631857

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation....

Introduction To Evolutionary Computing

DOWNLOAD
Author by : A.E. Eiben
Languange Used : en
Release Date : 2015-07-01
Publisher by : Springer

ISBN : 9783662448748

The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized the material to focus on problems, how to represent them, and then how to choose and design algorithms for different representations. They also added a chapter on problems, reflecting the overall book focus on problem-solvers, a chapter on parameter tuning, which they combined with the parameter control and "how-to" chapters into a methodological part, and finally a chapter on evolutionary robotics with an outlook on possible exciting developments in this field. The book is suitable for undergraduate and graduate courses in artificial intelligence and computational intelligence, and for self-study by practitioners and researchers engaged with all aspects of bioinspired design and optimization....

Introduction To Genetic Algorithms

DOWNLOAD
Author by : S.N. Sivanandam
Languange Used : en
Release Date : 2007-10-24
Publisher by : Springer Science & Business Media

ISBN : 9783540731900

This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields....

Evolutionary Computation For Modeling And Optimization

DOWNLOAD
Author by : Daniel Ashlock
Languange Used : en
Release Date : 2006-04-04
Publisher by : Springer Science & Business Media

ISBN : 9780387319094

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 Optimization

DOWNLOAD
Author by : Ruhul Sarker
Languange Used : en
Release Date : 2006-04-11
Publisher by : Springer Science & Business Media

ISBN : 9780306480416

Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization....

Applied Evolutionary Algorithms In Java

DOWNLOAD
Author by : Robert Ghanea-Hercock
Languange Used : en
Release Date : 2013-03-20
Publisher by : Springer Science & Business Media

ISBN : 9780387216157

This book is intended for students, researchers, and professionals interested in evolutionary algorithms at graduate and postgraduate level. No mathematics beyond basic algebra and Cartesian graphs methods is required, as the aim is to encourage applying the JAVA toolkit to develop an appreciation of the power of these techniques....

Evolutionary Intelligence

DOWNLOAD
Author by : S. Sumathi
Languange Used : en
Release Date : 2008-05-15
Publisher by : Springer Science & Business Media

ISBN : 9783540753827

This book provides a highly accessible introduction to evolutionary computation. It details basic concepts, highlights several applications of evolutionary computation, and includes solved problems using MATLAB software and C/C++. This book also outlines some ideas on when genetic algorithms and genetic programming should be used. The most difficult part of using a genetic algorithm is how to encode the population, and the author discusses various ways to do this....

Evolutionary Algorithms In Management Applications

DOWNLOAD
Author by : Jörg Biethahn
Languange Used : en
Release Date : 2012-12-06
Publisher by : Springer Science & Business Media

ISBN : 9783642612176

Evolutionary Algorithms (EA) are powerful search and optimisation techniques inspired by the mechanisms of natural evolution. They imitate, on an abstract level, biological principles such as a population based approach, the inheritance of information, the variation of information via crossover/mutation, and the selection of individuals based on fitness. The most well-known class of EA are Genetic Algorithms (GA), which have received much attention not only in the scientific community lately. Other variants of EA, in particular Genetic Programming, Evolution Strategies, and Evolutionary Programming are less popular, though very powerful too. Traditionally, most practical applications of EA have appeared in the technical sector. Management problems, for a long time, have been a rather neglected field of EA-research. This is surprising, since the great potential of evolutionary approaches for the business and economics domain was recognised in pioneering publications quite a while ago. John Holland, for instance, in his seminal book Adaptation in Natural and Artificial Systems (The University of Michigan Press, 1975) identified economics as one of the prime targets for a theory of adaptation, as formalised in his reproductive plans (later called Genetic Algorithms)....