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Cyclic shift genetic algorithm applied to design optimization of electromagnetic devices

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5 Author(s)
Chen Tanggong ; Province-Minist. Joint Key Lab. of Electromagn. Field, Hebei Univ. of Technol., Tianjin ; Wang Youhua ; Liu Zibin ; Shu Qunfang
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Based on the analysis of the premature convergence causing in genetic algorithm, and enlightened by the biology migratory phenomenon and Inversion Operator, a cyclic shift genetic algorithm (CSGA) was presented and discussed with different strategy. CSGA can effectively suppress the premature phenomenon of standard genetic algorithm (SGA), decrease the dependence of SGA to the character of initial population, and enhance the convergent speed and rate. The superiority of propose algorithm was validated by simulation and the successful application to the optimal design of electromagnetic devices.

Published in:

Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on

Date of Conference:

17-20 Oct. 2008