Practical Genetic Algorithms [With CDROM]

By Randy L. Haupt and Sue Ellen Haupt

Book Overview

* This book deals with the fundamentals of genetic algorithms and their applications in a variety of different areas of engineering and science
* Most significant update to the second edition is the MATLAB codes that accompany the text
* Provides a thorough discussion of hybrid genetic algorithms
* Features more examples than first edition

• Format: Hardcover
• Language: English
• ISBN: 0471455652
• ISBN13: 9780471455653
• Release Date: May 2004
• Publisher: Wiley-Interscience
• Length: 288 Pages
• Weight: 1.20 lbs.
• Dimensions: 0.7" x 6.1" x 9.5"

Customer Reviews

Great

In my opinion to well understand a process/method you have to follow an example in every little detail. This book does exactly this and once read allows to write your own code easily. I highly recommend this book!

Great Introduction For The Workplace or Classroom

This is a really good 'hands on' introduction to genetic algorithms. Mitchell gives a great introduction as well, but this book gets into the 'practical' side of it.Haupt^2's book starts off with an introduction. The ideas behind optimization are covered briefly (~20pgs). The book then proceeds into the ideas behind binary genetics (also introducing the evolutionary ideas ~25 pgs). The book then goes into developing the code itself, while describing the trade offs. Very good examples under applications are given (both basic and advanced ~40pgs). More sophisticated techniques are developed, with a wrap up on current trends in GA.A great intro book (undergrad *even high school*), and a friend to the working scientist/engineer. This is a book that'll help get the job done.

GA was much simpler than I thought.

Before I read this book, I had heard about GA and had an idea about how it works, but had no clue to actually coding it. One day I bought this book and spent a day to read it. On the following day, I was able to write my own GA driver code!

Useful and thought provoking

This book is a good one for beginning GA programmers to start with. It provides sufficient detail for implementing both binary and continuous GAs, and compares their performance throughout the book. The applications described are diverse and interesting, although some of the engineering applications were hard for me to follow. In short, I found this book interesting and full of good ideas to experiment with.

Practical and easy to read

I found this book to be an extremely clear and easy to understand introduction to genetic algorithms. It was particularly helpful to see examples of both binary and continuous versions of genetic algorithms, and to see explanations of examples on both elementary and advanced levels. This is a good book to read before buying one of the more comprehensive, rigorous technical books on the subject.