The Simple Genetic Algorithm: Foundations and Theory (Complex Adaptive Systems) [Hardcover]

Michael D. Vose (Author)

Book Description

Publication Date: August 27, 1999 | Series: Complex Adaptive Systems

The Simple Genetic Algorithm (SGA) is a classical form of genetic search. Viewing the SGA as a mathematical object, Michael D. Vose provides an introduction to what is known (i.e., proven) about the theory of the SGA. He also makes available algorithms for the computation of mathematical objects related to the SGA. Although he describes the SGA in terms of heuristic search, the book is not about search or optimization per se. Rather, the focus is on the SGA as an evolutionary system. The author intends the book also to serve as an outline for exploring topics in mathematics and computer science in a goal-oriented way.

Editorial Reviews

Amazon.com Review

It might be simple, but it's not easy. Computer scientist Michael D. Vose takes a rigorous look at The Simple Genetic Algorithm and shows the state of our knowledge in a book appropriate for advanced undergraduates, graduate students, and professionals.

Vose has decided to approach his subject as a mathematical object, keeping his discussion to a minimum and relying on mathematical demonstrations of what has been proven about this powerful genetic search. This approach maximizes the book's utility for its scope of readers; since each chapter builds on the material before, it makes a good teaching tool, but it is still a useful reference as the indexing helps the professional find proofs quickly.

Covering the basics of random heuristic searching and the nature of the algorithm, the book moves on to computing, transient and asymptotic behavior, models, and schemata. Cutting all of the material down to the basic provable theorems is not, as Vose admits, without problems: any speculation beyond these stripped-down proofs is left to the imaginative reader. But the intrepid explorer couldn't ask for firmer ground from which to launch flights of discovery, and genetic computation currently offers the widest frontiers. --Rob Lightner

Review

"This book should be required reading for anyone working in the theory of genetic algorithms and evolutionary computation."
—Alden Wright, Professor of Computer Science, University of Montana, Missoula

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Product Details

• Hardcover: 220 pages
• Publisher: The MIT Press (August 27, 1999)
• Language: English
• ISBN-10: 026222058X
• ISBN-13: 978-0262220583
• Product Dimensions: 9 x 7.2 x 0.9 inches
• Shipping Weight: 1.6 pounds
• Average Customer Review: 4.0 out of 5 stars  See all reviews (5 customer reviews)
• Amazon Best Sellers Rank: #2,682,024 in Books (See Top 100 in Books)
  • #67 in Books > Computers & Technology > Programming > Algorithms > Genetic

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Customer Reviews

Most Helpful Customer Reviews

12 of 12 people found the following review helpful:

4.0 out of 5 stars A mathematical introduction to Genetic Algorithms, May 24, 2002

By 

John (Canada) - See all my reviews

This review is from: The Simple Genetic Algorithm: Foundations and Theory (Complex Adaptive Systems) (Hardcover)

This book is for mathematicians or people who want to study genetic algorithms formally. If you are looking for a book that does not emphasize on the mathematical aspects and talks about parallels between genetic algorithms and natural selection,etc., then you should buy the books written by Goldberg or Mitchell.

It is a great introduction to genetic algorithms for advanced undergraduate mathematics students or people with sufficient math knowledge and maturity. If you read it without these prerequisites, you will only be able to understand little bits and will get lost in the formalism.

Prior knowledge of genetic algorithms is recommended. I did not give this book the perfect rating because I find that the author should introduce concepts intuitively before giving their mathematical definitions. I am aware that this can be a consequence of a lack of mathematical maturity on my part. If you are tired of reading books on genetic algorithms that talk about natural selection,etc. but do not formalize the concepts involved, then this a book for you.

3 of 3 people found the following review helpful:

5.0 out of 5 stars one of a kind modern classic, April 25, 2003

By 

"greatthinker" (USA) - See all my reviews

This review is from: The Simple Genetic Algorithm: Foundations and Theory (Complex Adaptive Systems) (Hardcover)

This book is the result of the author's attempts to "really understand" evolutionary algorithms. It's very mathematical and rigorous, though sometimes the formulation is not very usual. ( a warning!) You may need a few references, and pondering.

Is this a perfect book? Maybe not. But it's very important for the deeper understanding of GA...a landmark great job!

All people who are interested in the underpinning of GA should get this book. It's also a good supplement for mathematical modeling in the sense that it presents a very hard topic that few people have tried to formulate. I mean a very good demonstration of modeling complicated structures like heuristic learning process. And also a good supplement of general dynamical systems.

The style is kind of Dirac-like -- few words, short, original but you barely can add more words to the margins. It's a kind of modernized Chinese meal -- less oily, but still nutritious!! I cannot find any annoying and useless aside in the whole book.

The book is beautiful and well-bound, and nice paper, cover, etc. I got the hardback, though.

9 of 12 people found the following review helpful:

4.0 out of 5 stars dense but informative, January 8, 2001

By 

Jason Nordwick "jnordwick" (Pasadena, CA USA) - See all my reviews
(REAL NAME)   

This review is from: The Simple Genetic Algorithm: Foundations and Theory (Complex Adaptive Systems) (Hardcover)

the word simple in the title can be misleading. it is not meant to give the impression that the material in the book is simple, but to say that the topic covered is reduced to the simpliest of genetic algorithm theory, and then, you are brutally raked over burning coals by it.

the introduction given by the author could be mistaken as elitest, totalitarial propaganda for the next mathematical reich: condeming the application and biological euphamism that has been used to explain genetic algorithms while carrying the flag of pure mathematical abstraction. basically, all math and no play makes jack a dull boy, at least to those who wanted a simple introduction.

i found the math sometimes unnecessarily complex at times, with notation being abused (ironically, the author in the introduction condems those that do this, too), and the level of rigor being uneven. all of this makes it sometimes difficult to follow. but, there are some sections that where there is no better explanation in any book but the detailed, well thought out, straight forward presentation here (look at the coverage of walsh and the complex examples sections).

for anybody who uses ga's daily, this is an essential read for a truly deep understanding. the two friends that i have loaned this book to, returned it in under a month scared away by the mathematics, prima facie; it really isn't that bad and the understanding you get from this book is unparalled by any other dna-glossy-picture, darwinian-explanation filled excuse for a book.