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Electromagnetic Optimization
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Authoritative coverage of a revolutionary technique for overcoming problems in electromagnetic design Genetic algorithms are stochastic search procedures modeled on the Darwinian concepts of natural selection and evolution. The machinery of genetic algorithms utilizes an optimization methodology that allows a global search of the cost surface via statistical random processes dictated by the Darwinian evolutionary concept. These easily programmed and readily implemented procedures robustly locate extrema of highly multimodal functions and therefore are particularly well suited to finding solutions to a broad range of electromagnetic optimization problems. Electromagnetic Optimization by Genetic Algorithms is the first book devoted exclusively to the application of genetic algorithms to electromagnetic device design. Compiled by two highly competent and well-respected members of the electromagnetics community, this book describes numerous applications of genetic algorithms to the design and optimization of various low- and high-frequency electromagnetic components. Special features include:
* Introduction by David E. Goldberg, "A Meditation on the Application of Genetic Algorithms"
* Design of linear and planar arrays using genetic algorithms
* Application of genetic algorithms to the design of broadband, wire, and integrated antennas
* Genetic algorithm-driven design of dielectric gratings and frequency-selective surfaces
* Synthesis of magnetostatic devices using genetic algorithms
* Application of genetic algorithms to multiobjective electromagnetic backscattering optimization
* A comprehensive list of the up-to-date references applicable to electromagnetic design problems
Supplemented with more than 250 illustrations, Electromagnetic Optimization by Genetic Algorithms is a powerful resource for electrical engineers interested in modern electromagnetic designs and an indispensable reference for university researchers.
- Sales Rank: #4212045 in Books
- Published on: 1999-07-23
- Original language: English
- Number of items: 1
- Dimensions: 9.53" h x 1.13" w x 6.44" l, 1.78 pounds
- Binding: Hardcover
- 512 pages
Review
"...a powerful resource..." (Zentralblatt Math, Vol.992, No.17, 2002)
From the Back Cover
Authoritative coverage of a revolutionary technique for overcoming problems in electromagnetic design Genetic algorithms are stochastic search procedures modeled on the Darwinian concepts of natural selection and evolution. The machinery of genetic algorithms utilizes an optimization methodology that allows a global search of the cost surface via statistical random processes dictated by the Darwinian evolutionary concept. These easily programmed and readily implemented procedures robustly locate extrema of highly multimodal functions and therefore are particularly well suited to finding solutions to a broad range of electromagnetic optimization problems. Electromagnetic Optimization by Genetic Algorithms is the first book devoted exclusively to the application of genetic algorithms to electromagnetic device design. Compiled by two highly competent and well-respected members of the electromagnetics community, this book describes numerous applications of genetic algorithms to the design and optimization of various low- and high-frequency electromagnetic components. Special features include:
* Introduction by David E. Goldberg, "A Meditation on the Application of Genetic Algorithms"
* Design of linear and planar arrays using genetic algorithms
* Application of genetic algorithms to the design of broadband, wire, and integrated antennas
* Genetic algorithm-driven design of dielectric gratings and frequency-selective surfaces
* Synthesis of magnetostatic devices using genetic algorithms
* Application of genetic algorithms to multiobjective electromagnetic backscattering optimization
* A comprehensive list of the up-to-date references applicable to electromagnetic design problems
Supplemented with more than 250 illustrations, Electromagnetic Optimization by Genetic Algorithms is a powerful resource for electrical engineers interested in modern electromagnetic designs and an indispensable reference for university researchers.
About the Author
YAHYA RAHMAT-SAMII, PhD, is Professor of Electrical Engineering at the University of California, Los Angeles. ERIC MICHIELSSEN, PhD, is a professor in the Department of Electrical and Computer Engineering at the University of lllinois at Urbana-Champaign.
Most helpful customer reviews
0 of 0 people found the following review helpful.
A Good Resource
By A Customer
This book is well worth the price I paid for it.
It is a good book for engineers looking for practical information on genetic algorithms. The book assumes familiarity with electromagnetic theory, practical problems, and current simulation techniques.
The first three introductory chapters are solid, and universally applicable. They are a beginning overview of genetic algorithms, a more serious treatment describing pitfalls and variant techniques, and finally some rules of thumb for using the techniques.
The following chapters are detailed treatments of the application of genetic algorithms to real problems. Seven chapters are devoted to various types of antennas and antenna arrays. Additional chapters cover specific devices, such as electromagnetic filters, diffraction gratings, backscattering problems and magnetostatic devices.
This book will not teach you how to write genetic algorithm codes line by line. This book will not go into extreme depths about the theoretical limits and performance of genetic algorithms (where given, these details are not derived, simply given and explained.) There are any number of computer science and programming books which do that.
This is an engineering book: it will give many implementation details on practical problems, along with the results.
0 of 0 people found the following review helpful.
Great Book - Agree With Other Reviews
By A Customer
This book does live up to the expectations I had. The first three chapters are a very solid introduction to genetic algorithms. It also goes into variations that lets one overcome some of the 'stagnation' that can occur in GAs.
The rest of the book does dive into applying GAs to EM applications. They have a very good introduction of the motivation, problems encountered and how it was resolved. No code is available, but many have already written GAs in many programming languages.
Book assumes some knowledge in math (~calculus) and electrical engineering (my background is in physics, but it didn't handicap me). A must for anyone interested in EM design while integrating GAs or for anyone interested in applying GAs to their engineering problems.
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