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.
Newton's method reduces to steepest descent when the Hessian matrix is the identity matrix. Several iterative methods have been developed to estimate the Hessian matrix with the estimate getting closer after every iteration.
This book is intended to be a cookbook for students and researchers to understand the finite element method and optimization methods and couple them to effect shape optimization.
A thorough and insightful introduction to using genetic algorithms to optimize electromagnetic systems Genetic Algorithms in Electromagnetics focuses on optimizing the objective function when a computer algorithm, analytical model, or ...
A collection of state-of-the-art lectures by experts in the field of theoretical, numerical and applied aspects of genetic algorithms for the computational treatment of continuous, discrete and combinatorial optimization problems....
This book presents some of the emerging evolutionary algorithms (EAs) and their variants.
After this bi-annual event, a large number of papers were assembled and combined in this book. During the workshop recent developments and applications in optimization and inverse methodologies for electromagnetic fields were discussed.
This book is intended to be a cookbook for students and researchers to understand the finite element method and optimization methods and couple them to effect shape optimization.
Thus, this volume touches on what is of key importance in electromagnetism.
Schlick T (2002) Molecular Modeling and Simulation, Springer. Schulze-Kremer S (2006) Genetic Algorithms and Protein Folding, http://www. techfak.uni-bielefeld.de/bcd/Curric/ProtEn/proten.html, March Shmygelska A, Hoos H H (2005) An ant ...
The book addresses some of the most recent issues, with the theoretical and methodological aspects, of evolutionary multi-objective optimization problems and the various design challenges using different hybrid intelligent approaches.