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Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Ge by Kaisa Miettinen, Evolutionary Algorithms in Engineering engine natural optimization search and Computer Science Edited by K. Miettinen, University of Jyvaskyla, Finland M. M. Makela, University of Jyvaskyla, Finland P. Neittaanmaki, University of Jyvaskyla, Finland J. Periaux, Dassault Aviation, France What is Evolutionary Computing? Based on the genetic message encoded in DNA, engine natural optimization search and digitalized algorithms inspired by the Darwinian framework of evolution by natural selection, Evolutionary Computing is one of the most important information technologies of our times. Evolutionary algorithms encompass all adaptive engine natural optimization search and computational models of natural evolutionary systems - genetic algorithms, evolution strategies, evolutionary programming engine natural optimization search and genetic programming. In addition, they work well in the search for global solutions to optimization problems, allowing the production of optimization software that is robust engine natural optimization search and easy to implement. Furthermore, these algorithms can easily be hybridized with traditional optimization techniques. This book presents state-of-the-art lectures delivered by international academic engine natural optimization search and industrial experts in the field of evolutionary computing. It bridges artificial intelligence engine natural optimization search and scientific computing with a particular emphasis on real-life problems encountered in application-oriented sectors, such as aerospace, electronics, telecommunications, energy engine natural optimization search and economics. This rapidly growing field, with its deep understanding engine natural optimization search and assesssment of complex problems in current practice, provides an effective, modern engineering tool. This book will therefore be of significant interest engine natural optimization search and value to all postgraduates, research scientists engine natural optimization search and practitioners facing complex optimization problems. CLICK HERE Electromagnetic Optimization by Genetic Algorithms by Yahya Rahmat-Samii, 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 engine natural optimization search 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 engine natural optimization search and readily implemented procedures robustly locate extrema of highly multimodal functions engine natural optimization search 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 engine natural optimization search and well-respected members of the electromagnetics community, this book describes numerous applications of genetic algorithms to the design engine natural optimization search and optimization of various low- engine natural optimization search and high-frequency electromagnetic components. Special features include: Introduction by David E. Goldberg, " A Meditation on the Application of Genetic Algorithms" Design of linear engine natural optimization search and planar arrays using genetic algorithmsApplication of genetic algorithms to the design of broadband, wire, engine natural optimization search and integrated antennasGenetic algorithm— driven design of dielectric gratings engine natural optimization search and frequency-selective surfacesSynthesis of magnetostatic devices using genetic algorithmsApplication of genetic algorithms to multiobjective electromagnetic backscattering optimizationA comprehensive list of the up-to-date references applicable to electromagnetic design problemsSupplementedwith more than 250 illustrations, Electromagnetic Optimization by Genetic Algorithms is a powerful resource for electrical engineers interested in modern electromagnetic designs engine natural optimization search and an indispensable reference for university researchers. CLICK HERE

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