When looking for a perfect text to match your needs , especially for beginner and intermediate studies, Practical Genetic Algorithms Haupt – 2nd Edition book pdf is all you need. Scope , content ,relevant topics, easy to understand examples and good enough question. This book is written by seasoned and experienced professional and the pdf format makes it easy to asses  on your phones, tablets or laptops. This gem and other relevant texts are available for free on this PDF website

About The practical genetic algorithms haupt pdf Book

* This practical-genetic-algorithms-pdf book deals with the fundamentals of genetic algorithms andtheir applications in a variety of different areas of engineeringand science
* Most significant update to the second edition is the MATLAB codesthat accompany the text
* Provides a thorough discussion of hybrid genetic algorithms
* Features more examples than first edition

TABLE OF CONTENTS

Preface.

Preface to First Edition.

List of Symbols.

1. Introduction to Optimization.

1.1 Finding the Best Solution.

1.2 Minimum-Seeking Algorithms.

1.3 Natural Optimization Methods.

1.4 Biological Optimization: Natural Selection.

1.5 The Genetic Algorithm.

2. The Binary Genetic Algorithm.

2.1 Genetic Algorithms: Natural Selection on a Computer.

2.2 Components of a Binary Genetic Algorithm.

2.3 A Parting Look.

3. The Continuous Genetic Algorithm.

3.1 Components of a Continuous Genetic Algorithm.

3.2 A Parting Look.

4. Basic Applications.

4.1 “Mary Had a Little Lamb”.

4.2 Algorithmic Creativity-Genetic Art.

4.3 Word Guess.

4.4 Locating an Emergency Response Unit.

4.5 Antenna Array Design.

4.6 The Evolution of Horses.

4.7 Summary.

5. An Added Level of Sophistication.

5.1 Handling Expensive Cost Functions.

5.2 Multiple Objective Optimization.

5.3 Hybrid GA.

5.4 Gray Codes.

5.5 Gene Size.

5.6 Convergence.

5.7 Alternative Crossovers for Binary GAs.

5.8 Population.

5.9 Mutation.

5.10 Permutation Problems.

5.11 Selling GA Parameters.

5.12 Continuous versus Binary GA.

5.13 Messy Genetic Algorithms.

5.14 Parallel Genetic Algorithms.

6. Advanced Applications.

6.1 Traveling Salespersons Problem.

6.2 Locating an Emergency Response Unit Revisited.

6.3 Decoding a Secret Message.

6.4 Robot Trajectory Planning.

6.5 Stealth Design.

6.6 Building Dynamical Inverse Models-The Linear Case.

6.7 Building Dynamical Inverse Models-The Nonlinear Case.

6.8 Combining GAs with Simulations-Air Pollution Receptor Modeling.

6.9 Combining Methods Neural Nets with GAs.

6.10 Solving High-Order Nonlinear Partial Differential Equations.

7. More Natural Optimization Algorithms.

7.1 Simulated Annealing.

7.2 Particle Swarm Optimization (PSO).

7.3 Ant Colony Optimization (ACO).

7.4 Genetic Programming (GP).

7.5 Cultural Algorithms.

7.6 Evolutionary Strategies.

7.7 The Future of Genetic Algorithms.

Appendix I: Test Functions.

Appendix II: MATLAB Code.

Appendix III. High-Performance Fortran Code.

Glossary.

Index.

practical genetic algorithms pdf

practical genetic algorithms haupt 2nd edition pdf download
practical genetic algorithms haupt 2nd edition pdf free

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