Practical Genetic Algorithms

Randy L. Haupt, Sue Ellen Haupt

253 pages, parution le 01/07/2004 (2^eme édition)

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Résumé

The use of genetic algorithms (GAs) to solve large and often complex computational problems has given rise to many new applications in a variety of disciplines. Practical Genetic Algorithms was the first introductory-level book on genetic algorithms to emphasize practical applications rather than theory. Practical Genetic Algorithms, Second ttition reflects the significant evolution of the field since the book's first edition.

In an accessible style, the authors explain why the genetic algorithm is superior in many real-world applications, cover continuous parameter genetic algorithms, and provide in-depth trade-off analysis of genetic algorithm parameter selection. This Second [Urn features:
Numerous practical example problems
A CD-ROM with MATLAB and High Performance Fortran codes
R, more complete picture of traditional optimization d examples reflecting recent research ige of pareto-genetic and hybrid genetic algorithms (GAs)
New sections on hybrid GAs, parallel GAs, and messy GAs, with recommendations on improving their performance
An all new chapter on simulated annealing, ant-colony optimization, evolutionary strategies, and other cutting-edge artificial intelligence methods of optimization

Written for the practicing scientist, engineer, economist, artist, or anyone with an interest in the basics of GAs, the Second Edition continues to offer readers an up-to-date look at the evolving practical applications of GAs and how to manipulate them in order to get the best performance.

L'auteur - Randy L. Haupt

Randy L. Haupt is Department Head and Senior Scientist at The Pennsylvania State University Applied Research Laboratory, State College, Pennsylvania.

L'auteur - Sue Ellen Haupt

Sue Ellen Haupt, PhD, is a Senior Research Associate in the Computational Mechanics Division of The Pennsylvania State University Applied Research Laboratory, State College, Pennsylvania.

Sommaire

Introduction to Optimization
The Binary Genetic Algorithm
The Continuous Genetic Algorithm
Basic Applications
An Added Level of Sophistication
Advanced Applications
More Natural Optimization Algorithms
Appendix I: Test Functions
Appendix II: MATLAB Code
Appendix III High-Performance Fortran Code

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Randy L. Haupt, Sue Ellen Haupt
Parution	01/07/2004
Édition	2^eme édition
Nb. de pages	253
Format	16 x 24
Couverture	Relié
Poids	530g
Intérieur	Noir et Blanc
EAN13	9780471455653
ISBN13	978-0-471-45565-3

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