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A stop criterion to accelerate magnetic optimization process using genetic algorithms and finite element analysis

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3 Author(s)
Hajji, O. ; Ecole Centrale de Lille, Villeneuve d''Ascq, France ; Brisset, S. ; Brochet, P.

In this paper, a new stop criterion is proposed for genetic algorithms using a response surface fitted on the best individuals. This criterion is tested on a superconducting magnetic energy storage optimization and compared with stop criteria found in the literature that are reviewed and detailed.

Published in:

Magnetics, IEEE Transactions on  (Volume:39 ,  Issue: 3 )