Graduate School of Information Science and Technology, Hokkaido University
Electromagnetic field (EM) computation has widely been used for performance analysis of electric machines and analysis of electromagnetic phenomena. On the other hand, evolutionary computations using e.g. genetic algorithm (GA) have rapidly been prevailed in engineering because (1) global search can be done without dependence on initial solutions (2) differentiability of objective function is not required (3) complicated restriction can be easily imposed (4) multi-objective optimization is easily carried out. Combining EM field computation and evolutionary computation, we can realize optimization by which we can maximize the machine performance. Moreover, using this method, we can also perform topology and robust optimizations. In this talk, the fundamentals of GA and its state-of-the-art applications will be presented.
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