Evolutionary Electronics

From the explosion of interest, research, and applications of evolutionary computation a new field emerges-evolutionary electronics. Focused on applying evolutionary computation concepts and techniques to the domain of electronics, many researchers now see it as holding the greatest potential for overcoming the drawbacks of conventional design techniques. Evolutionary Electronics: Automatic Design of Electronic Circuits and Systems by Genetic Algorithms formally introduces and defines this area of research, presents its main challenges in electronic design, and explores emerging technologies. It describes the evolutionary computation paradigm and its primary algorithms, and explores topics of current interest, such as multi-objective optimization. The authors examine numerous evolutionary electronics applications, draw conclusions about those applications, and sketch the future of evolutionary computation and its applications in electronics. In coming years, the appearance of more and more advanced technologies will increase the complexity of optimization and synthesis problems, and evolutionary electronics will almost certainly become a key to solving those problems. Evolutionary Electronics is your key to discovering and unlocking the potential of this promising new field.

From the explosion of interest, research, and applications of evolutionary computation a new field emerges-evolutionary electronics. Focused on applying evolutionary computation concepts and techniques to the domain of electronics, many researchers now see it as holding the greatest potential for overcoming the drawbacks of conventional design techniques.Evolutionary Electronics: Automatic Design of Electronic Circuits and Systems by Genetic Algorithms formally introduces and defines this area of research, presents its main challenges in electronic design, and explores emerging technologies. It describes the evolutionary computation paradigm and its primary algorithms, and explores topics of current interest, such as multi-objective optimization. The authors examine numerous evolutionary electronics applications, draw conclusions about those applications, and sketch the future of evolutionary computation and its applications in electronics. In coming years, the appearance of more and more advanced technologies will increase the complexity of optimization and synthesis problems, and evolutionary electronics will almost certainly become a key to solving those problems.; Evolutionary Electronics is your key to discovering and unlocking the potential of this promising new field.

This volume provides practicing engineers with new solutions to demanding real-world problems. It presents applications of soft computing to the field of industrial electronics in two categories, electric power applications and emerging applications.

Evolutionary Computation (EC) includes a number of techniques such as Genetic Algorithms which have been used in a diverse range of highly successful applications. This book brings together some of these EC applications in fields including electronics, telecommunications, health, bioinformatics, supply chain and other engineering domains, to give the audience, including both EC researchers and practitioners, a glimpse of this exciting and rapidly-evolving field.

Evolution through natural selection has been going on for a very long time. Evolution through artificial selection has been practiced by humans for a large part of our history, in the breeding of plants and livestock. Artificial evolution, where we evolve an artifact through artificial selection, has been around since electronic computers became common: about 30 years. Right from the beginning, people have suggested using artificial evolution to design electronics automatically.l Only recently, though, have suitable re configurable silicon chips become available that make it easy for artificial evolution to work with a real, physical, electronic medium: before them, ex periments had to be done entirely in software simulations. Early research concentrated on the potential applications opened-up by the raw speed ad vantage of dedicated digital hardware over software simulation on a general purpose computer. This book is an attempt to show that there is more to it than that. In fact, a radically new viewpoint is possible, with fascinating consequences. This book was written as a doctoral thesis, submitted in September 1996. As such, it was a rather daring exercise in ruthless brevity. Believing that the contribution I had to make was essentially a simple one, I resisted being drawn into peripheral discussions. In the places where I deliberately drop a subject, this implies neither that it's not interesting, nor that it's not relevant: just that it's not a crucial part of the tale I want to tell here.

Industrial electronics systems govern so many different functions that vary in complexity-from the operation of relatively simple applications, such as electric motors, to that of more complicated machines and systems, including robots and entire fabrication processes. The Industrial Electronics Handbook, Second Edition combines traditional and new

A comprehensive introduction to new approaches in artificial intelligence and robotics that are inspired by self-organizing biological processes and structures. New approaches to artificial intelligence spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development, and learning. Traditionally, artificial intelligence has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wider range of biological structures that that are capable of autonomous self-organization. Examples of these new approaches include evolutionary computation and evolutionary electronics, artificial neural networks, immune systems, biorobotics, and swarm intelligence—to mention only a few. This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers. Each chapter presents computational approaches inspired by a different biological system; each begins with background information about the biological system and then proceeds to develop computational models that make use of biological concepts. The chapters cover evolutionary computation and electronics; cellular systems; neural systems, including neuromorphic engineering; developmental systems; immune systems; behavioral systems—including several approaches to robotics, including behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and collective systems, including swarm robotics as well as cooperative and competitive co-evolving systems. Chapters end with a concluding overview and suggested reading.

This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book’s second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.