Efficient and Accurate Parallel Genetic Algorithms (Genetic Algorithms and Evolutionary Computation)
| Author | : | |
| Rating | : | 4.23 (586 Votes) |
| Asin | : | 1461369649 |
| Format Type | : | paperback |
| Number of Pages | : | 162 Pages |
| Publish Date | : | 2017-08-01 |
| Language | : | English |
DESCRIPTION:
"Still the best analysis around." according to 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 av. "Thorough review and new results" according to 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 ass. Misleading title A Customer 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 mus
In such cases, parallel implementations of GAs become necessary to reach high-quality solutions in reasonable times. 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 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. Those who are ready to try a parallel GA on their applications may choose to skim through the background material, and use the results
`I urgently recommend that all readers interested in parallel genetic and evolutionary algorithms study this important book carefully and soon.'David Goldberg