DocumentCode :
786953
Title :
Hybrid genetic algorithm for electromagnetic topology optimization
Author :
Im, Chang-Hwan ; Jung, Hyun-Kyo ; Kim, Yong-Joo
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Seoul Nat. Univ., South Korea
Volume :
39
Issue :
5
fYear :
2003
Firstpage :
2163
Lastpage :
2169
Abstract :
This paper proposes a hybrid genetic algorithm (GA) for electromagnetic topology optimization. A two-dimensional (2-D) encoding technique, which considers the geometrical topology, is first applied to electromagnetics. Then, a 2-D geographic crossover is used as the crossover operator. A novel local optimization algorithm, called the on/off sensitivity method, hybridized with the 2-D encoded GA, improves the convergence characteristics. The algorithm was verified by applying it to various case studies, and the results are presented herein.
Keywords :
brushless DC motors; convergence; electromagnetic field theory; genetic algorithms; machine theory; magnetoencephalography; 2-D geographic crossover; brushless DC motor optimization; convergence characteristics; crossover operator; current source optimization problem; electromagnetic topology optimization; geometrical topology; hybrid genetic algorithm; local optimization algorithm; magnetoencephalography source localization problem; on/off sensitivity method; reduced cogging torque; two-dimensional encoding technique; Application software; Circuit topology; Convergence; Design optimization; Electromagnetic devices; Encoding; Genetic algorithms; Optimization methods; Sensitivity analysis; Two dimensional displays;
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/TMAG.2003.817094
Filename :
1233027
Link To Document :
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