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Zbigniew Michalewicz

Genetic Algorithms + Data Structures = Evolution Programs Hardcover – January 1, 1996

by Zbigniew Michalewicz (Author)

8 ratings

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Print length

407 pages
Language

English
Publisher

Springer
Publication date

January 1, 1996
Dimensions

6.39 x 1 x 9.54 inches
ISBN-10

3540606769
ISBN-13

978-3540606765
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Editorial Reviews

Amazon.com Review

Zbigniew Michalewicz's Genetic Algorithms + Data Structures = Evolution Programs has three sections. The first section is a straightforward introduction to genetic algorithms. In the second section, Michalewicz describes how to apply genetic algorithms to numerical optimization. Michalewicz, who is a pioneer in this field, discusses the rationale for using genetic algorithms for numerical optimization and describes several experiments that show how this new type of genetic algorithm performs. The author devotes the third section of the book to evolution programs.

From the Back Cover

Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The aim of this book is to talk about the field of evolutionary computation in simple terms, and discuss the simplicity and elegance of its methods on many interesting test cases. The book may serve as a guide to writing an evolution program, and to making this an enjoyable experience. It is self-contained and the only prerequisite is basic undergraduate mathematics. Aimed at researchers, practitioners, and graduate students, it may serve as a text for advanced courses in computer science and artificial intelligence, operations research, and engineering. This third edition has been substantially revised and extended. Three new chapters discuss the recent paradigm of genetic programming, heuristic methods and constraint handling, and current directions of research. Additional appendices contain test functions for experiments with evolutionary techniques and discuss possible projects for use in a project-oriented course.

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Product details

Publisher : Springer; 3rd, rev. and extended ed. 1996. Corr. 2nd printing 1998 edition (January 1, 1996)
Language : English
Hardcover : 407 pages
ISBN-10 : 3540606769
ISBN-13 : 978-3540606765
Item Weight : 1.66 pounds
Dimensions : 6.39 x 1 x 9.54 inches

Best Sellers Rank: #2,445,629 in Books (See Top 100 in Books)
- #123 in Genetic Algorithms
- #125 in Data Structure and Algorithms
- #368 in Number Systems (Books)

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Joel

Concise roadmap.

Reviewed in the United States on May 22, 2016

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Broad overview of both classic genetic programming and the newer evolution programming on a large set of real world problems.

Helpful

Arnab Banerjee

Lot of ideas for Genetic and Evolutionary Algorithm

Reviewed in the United States on January 4, 2007

This book is not written to be the primary text book for a Genetic Algotithm, Data Structure or a Neural Algorithm course. However this book gives an excellent introduction to modern approaches to Evolutionary Algorithm, and how/whether GAs and EAa can be applied successfully to problems of Optimisation, Navigation, and also other contemporary and emerging fields.

This book emphasizes on a lot of fresh ideas (which already requires background in GA, and Algorithms) and may be highly recommended for reference reading of Evolutionary Algorithms and allied Techniques.

Helpful

J. Sheppard

Not a good overview text of the subject.

Reviewed in the United States on July 19, 1998

I used this book as the primary text for a graduate course on evolutionary computation. I was looking for a book that provided a good introduction to genetic algorithms and provided a wide cross-section of related algorithms and applications. At the time, this was the only book of its type on the market (other than Goldberg's book). The first couple of chapters (What is a GA, Why Does a GA Work) were pretty good, but then the strong focus of the remainder of the book on numerical optimization resulted in a loss of interest on the part of my students. Since then, I have had to re-organize the class to provide topics such as genetic programming, evolving neural systems, co-evolution, and artificial life -- none of which are covered adequately (if at all) in this book.

21 people found this helpful

Helpful

Maximus Meridius

could GA get possibly any eaiser to understand???

Reviewed in the United States on March 19, 2005

I saw this book once with one of my buddies,and read the first chapter,,,it was after looking up the first chapter i decided to buy it...I have read some other books on this topic,and since i was kinda in rush for a project which needed GA,i found no other book which explains the concepts and procedures, this straightforward and "right to the point".As far as writing this book goes, "Michalewicz" has done a really really great job.
Go for it guys!!!
cheers,
Amir

3 people found this helpful

Helpful

Jean-Michel Rogero

One of the best book on genetic algorithms

Reviewed in the United States on July 11, 2002

A very good vision of the evolutionary optimisation techniques not only GA. As well there is an excellent chapter on constraints handling. Maybe it is not one of the easiest book on GA but it is definitely the most useful.

One person found this helpful

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