Applied Evolutionary Algorithms in Java

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Springer Science & Business Media, 2013 M03 20 - 219 páginas
Genetic algorithms provide a powerful range of methods for solving complex engineering search and optimization algorithms. Their power can also lead to difficulty for new researchers and students who wish to apply such evolution-based methods. "Applied Evolutionary Algorithms in Java" offers a practical, hands-on guide to applying such algorithms to engineering and scientific problems. The concepts are illustrated through clear examples, ranging from simple to more complex problems domains; all based on real-world industrial problems. Examples are taken from image processing, fuzzy-logic control systems, mobile robots, and telecommunication network optimization problems. The Java-based toolkit provides an easy-to-use and essential visual interface, with integrated graphing and analysis tools. Topics and features: *inclusion of a complete Java toolkit for exploring evolutionary algorithms *strong use of visualization techniques, to increase understanding *coverage of all major evolutionary algorithms in common usage *broad range of industrially based example applications *includes examples and an appendix based on fuzzy logic This book is intended for students, researchers, and professionals interested in using evolutionary algorithms in their work. No mathematics beyond basic algebra and Cartesian graphs methods are required, as the aim is to encourage applying the Java toolkit to develop the power of these techniques.
 

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Contenido

Preface
1
Principles of Natural Evolution
19
Genetic Algorithms
27
Genetic Programming
47
Engineering Examples Using Genetic Algorithms
57
Future Directions in Evolutionary Computing
101
The Future of Evolutionary Computing
115
Bibliography 121
120
Appendix A
133
Appendix C
169
Appendix D
181
Physical Layout of ClientZero
207
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