Efficient and Accurate Parallel Genetic Algorithms (Genetic Algorithms and Evolutionary Computation 1) (Hardcover)

~ Erick Cantu-Paz (Author) "Genetic Algorithms (GAs) are search methods based on principles of natural selection and genetics..." (more)
Key Phrases: deme count, receiving deme, eight demes, Generations Generations Mig (more...)

Editorial Reviews

Review

`I urgently recommend that all readers interested in parallel genetic and evolutionary algorithms study this important book carefully and soon.' David Goldberg

Product Description

As genetic algorithms (GAs) become increasingly popular, they are applied to difficult problems that may require considerable computations. In such cases, parallel implementations of GAs become necessary to reach high-quality solutions in reasonable times. But, even though their mechanics are simple, parallel GAs are complex non-linear algorithms that are controlled by many parameters, which are not well understood. Efficient and Accurate Parallel Genetic Algorithms is about the design of parallel GAs. It presents theoretical developments that improve our understanding of the effect of the algorithm's parameters on its search for quality and efficiency. These developments are used to formulate guidelines on how to choose the parameter values that minimize the execution time while consistently reaching solutions of high quality. Efficient and Accurate Parallel Genetic Algorithms can be read in several ways, depending on the readers' interests and their previous knowledge about these algorithms. Newcomers to the field will find the background material in each chapter useful to become acquainted with previous work, and to understand the problems that must be faced to design efficient and reliable algorithms. Potential users of parallel GAs that may have doubts about their practicality or reliability may be more confident after reading this book and understanding the algorithms better. Those who are ready to try a parallel GA on their applications may choose to skim through the background material, and use the results directly without following the derivations in detail. These readers will find that using the results can help them to choose the type of parallel GA that best suits their needs, without having to invest the time to implement and test various options. Once that is settled, even the most experienced users dread the long and frustrating experience of configuring their algorithms by trial and error. The guidelines contained herein will shorten dramatically the time spent tweaking the algorithm, although some experimentation may still be needed for fine-tuning. Efficient and Accurate Parallel Genetic Algorithms is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.

Product Details

• Hardcover: 162 pages
• Publisher: Springer; 1st edition (December 15, 2000)
• Language: English
• ISBN-10: 0792372212
• ISBN-13: 978-0792372219
• Product Dimensions: 9.8 x 6.3 x 0.6 inches
• Shipping Weight: 15.7 ounces (View shipping rates and policies)
• Average Customer Review: 3.7 out of 5 stars  See all reviews (3 customer reviews)
• Amazon.com Sales Rank: #2,688,247 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

6 of 7 people found the following review helpful:

5.0 out of 5 stars Thorough review and new results, July 28, 2001

By A Customer

Genetic algorithms are easy to parallelize, but they are difficult to control. In a very concise manner, this book presents some theoretical results derived by the author that show how to make parallel genetic algoritms work for many problems and different architectures.

The book has a lot of new theory that is easy to follow and gives recommendations to make parallel genetic algorithms work well in many circumstances. Although the theory makes many simplyfying assumptions, the examples in the book demonstrate that the models are very accurate and the recommendations made in the book seem very reasonable.

2 of 2 people found the following review helpful:

5.0 out of 5 stars Still the best analysis around., June 23, 2004

By A Customer

I think the previous reviewer got it wrong: It is very clear from the editorial introduction and from the table of contents that this book is about the ANALYSIS of parallel genetic algorithms, not about their implementation. The problem here is that implementing these algorithms is relatively easy, but configuring them is very complicated because there are many parameters. The work of Cantu-Paz---excellently summarized in this little book---is the best analysis available for the different types of parallel genetic algorithms.

I recommend this book wholeheartedly.

1 of 4 people found the following review helpful:

1.0 out of 5 stars Misleading title, May 28, 2003

By	"cqhoward" (South Australia, Australia) - See all my reviews

One would have thought from the title of the book that it would contain "... Parallel Genetic Algorithms", however it does not. The book covers statistical analyses of algorithms. The reader is meant to find other references that contain algorithms. It is expensive for such a small book. The author talks 'around' the algorithms, without going into the necessary details to write your own parallel genetic algorithms. There are many plots of evolution, so the author must of had access to the algorithms. This book could have been so much more valuable if it contained the algorithms, rather than just talk about them.