Multiobjective Shape Design in Electricity and Magnetism
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Beschreibung
Multiobjective Shape Design in Electricity and Magnetism is entirely focused on electric and magnetic field synthesis, with special emphasis on the optimal shape design of devices when conflicting objectives are to be fulfilled. Direct problems are solved by means of finite-element analysis, while evolutionary computing is used to solve multiobjective inverse problems. This approach, which is original, is coherently developed throughout the whole manuscript. The use of game theory, dynamic optimisation, and Bayesian imaging strengthens the originality of the book.
Covering the development of multiobjective optimisation in the past ten years, Multiobjective Shape Design in Electricity and Magnetism is a concise, comprehensive and up-to-date introduction to this research field, which is growing in the community of electricity and magnetism. Theoretical issues are illustrated by practical examples. In particular, a test problem is solved by different methods so that, by comparison of results, advantages and limitations of the various methods are made clear.
Topics covered include:
Maxwell equations and boundary-value problems;
Paretian optimality;
static optimisation;
game theory;
dynamic optimisation;
Bayesian imaging.
Multiobjective Shape Design in Electricity and Magnetism collects the long-lasting experience matured by the author during his research activity both at the university and in cooperation with industrial laboratories.
Multiobjective Shape Design in Electricity and Magnetism is entirely focused on electric and magnetic field synthesis, with special emphasis on the optimal shape design of devices when conflicting objectives are to be fulfilled. Direct problems are solved by means of finite-element analysis, while evolutionary computing is used to solve multiobjective inverse problems. This approach, which is original, is coherently developed throughout the whole manuscript. The use of game theory, dynamic optimisation, and Bayesian imaging strengthens the originality of the book. Covering the development of multiobjective optimisation in the past ten years, Multiobjective Shape Design in Electricity and Magnetism is a concise, comprehensive and up-to-date introduction to this research field, which is growing in the community of electricity and magnetism. Theoretical issues are illustrated by practical examples. In particular, a test problem is solved by different methods so that, by comparison of results, advantages and limitations of the various methods are made clear.
The first book which uses game theory, dynamic optimisation and Bayesian imaging to solve design problems in electricity and magnetism A book in which field synthesis problems are solved by means of evolutionary computing A self-contained and up-to-date introduction to multiobjective design optimisation in electricity and magnetism A book in which multiple optimal solutions to problems of industrial electromagnetic design are proposed Based on a problem-solving approach which offers practical examples solved by various methods
Autor*in
Paolo Di Barba
Themen in »Multiobjective Shape Design in Electricity and Magnetism«
Electric And Magnetic Field Synthesis Evolutionary Computing Finite-Element Modelling Of Electric And Magnetic Devices HTS Magnetic field Maxwell equation Multiobjective Optimisation In Electricity And Magnetism Optimal Shape Design
Stimmen zu »Multiobjective Shape Design in Electricity and Magnetism«
"The intention of this book is to try to dispel some of the myths surrounding computer-based optimisation. Professor Di Barba provides an up-to-date and comprehensive overview of optimisation techniques related to electromagnetic devices and systems in a logical and consistent way. An understanding of the contents of this book can help a designer to use the computational resources that are now available in a much more effective manner."
David A. Lowther Ph.D., AKC, FCAE, FIET
James McGill Professor
Department of Electrical and Computer Engineering
McGill University, Montreal
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