Practical Genetic Algorithms [Hardcover]

Randy L. Haupt (Author), Sue Ellen Haupt (Author)

Book Description

ISBN-10: 0471188735 | ISBN-13: 978-0471188735 | Publication Date: January 5, 1998 | Edition: 1

A tutorial on genetic algorithms with an emphasis on practical applications

The rapidly expanding field of genetic algorithms has given rise to many new applications in a variety of disciplines. However, most of the existing books on the subject concentrate on theory. Practical Genetic Algorithms is the first introductory-level book to emphasize practical applications through the use of example problems.

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. Written for the end user in engineering, science, and computer programming, as well as upper-level undergraduate and graduate students, Practical Genetic Algorithms:
* Provides numerous practical example problems
* Contains over 80 illustrations
* Features many figures and tables
* Includes three appendices: a glossary of terms, a list of genetic algorithm routines in pseudocode, and a list of symbols used in the book.

Editorial Reviews

Review

"...the first introductory-level book to emphasize practical applications through the use of example problems..." (International Journal of General Systems, Vol. 31, No. 1, 2002)

From the Publisher

This well-organized, introductory text takes the reader through the new and rapidly expanding field of genetic algorithms step by step, from a discussion of numerical optimization, to a survey of current extensions to genetic algorithms and applications. For the first time, theory is linked to practical application in a variety of disciplines through the presentation of numerous examples. Includes a glossary of important terms and a list of some genetic algorithm routines in pseudocode.

See all Editorial Reviews

Product Details

• Hardcover: 192 pages
• Publisher: Wiley-Interscience; 1 edition (January 5, 1998)
• Language: English
• ISBN-10: 0471188735
• ISBN-13: 978-0471188735
• Product Dimensions: 9.5 x 6.4 x 0.7 inches
• Shipping Weight: 1.1 pounds
• Average Customer Review: 4.0 out of 5 stars  See all reviews (11 customer reviews)
• Amazon Best Sellers Rank: #2,782,872 in Books (See Top 100 in Books)
  • #78 in Books > Computers & Technology > Programming > Algorithms > Genetic

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Customer Reviews

Most Helpful Customer Reviews

18 of 18 people found the following review helpful:

5.0 out of 5 stars Useful and thought provoking, February 28, 1999

By A Customer

This review is from: Practical Genetic Algorithms (Hardcover)

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.

13 of 13 people found the following review helpful:

5.0 out of 5 stars Practical and easy to read, August 23, 1998

By 

Kip Irvine (Miami, FL USA) - See all my reviews
(REAL NAME)   

This review is from: Practical Genetic Algorithms (Hardcover)

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.

19 of 21 people found the following review helpful:

1.0 out of 5 stars Not a good place to start, July 26, 2002

By 

Chuanpu Hu (Cary, NC USA) - See all my reviews

This review is from: Practical Genetic Algorithms (Hardcover)

Presents non-standard techniques without pointing out the standard ones. The non-standard techniques were recommended strongly based only on author's personal opinions, without comparison to other standard techniques on broad spectrum.

For starters, it is much better to look into "An Introduction to Genetic Algorithms" by Melanie Michell.