DocumentCode
482957
Title
A novel adaptive genetic algorithm applied to optimizing linear induction machines
Author
Zhuang, Y.C. ; Yu, H.T. ; Hu, M.Q. ; Xia, Jun
Author_Institution
Dept. of Electr. Eng., Southeast Univ., Nanjing
fYear
2008
fDate
17-20 Oct. 2008
Firstpage
3435
Lastpage
3438
Abstract
A novel adaptive genetic algorithm (NAGA), which improves the global search ability and convergence of solutions by adjusting the crossover and mutation probability automatically, is presented for the design optimization of linear induction motors (LIM). Results by the proposed algorithm are compared with another algorithm to demonstrate the superiority and feasibility of the proposed NAGA.
Keywords
genetic algorithms; linear induction motors; machine theory; adaptive genetic algorithm; global search ability; linear induction machines optimization; Algorithm design and analysis; Aluminum; Design optimization; Genetic algorithms; Genetic mutations; Induction machines; Induction motors; Optimization methods; Stochastic processes; Topology; Adaptive genetic algorithm; Linear induction machines; Uniform design; optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-3826-6
Electronic_ISBN
978-7-5062-9221-4
Type
conf
Filename
4771361
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