Title :
A stop criterion to accelerate magnetic optimization process using genetic algorithms and finite element analysis
Author :
Hajji, Omessad ; Brisset, Stéphane ; Brochet, Pascal
Author_Institution :
Ecole Centrale de Lille, Villeneuve d´´Ascq, France
fDate :
5/1/2003 12:00:00 AM
Abstract :
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.
Keywords :
finite element analysis; genetic algorithms; response surface methodology; superconducting magnet energy storage; finite element analysis; genetic algorithm; magnetic device; optimization; response surface methodology; stop criterion; superconducting magnetic energy storage; Acceleration; Algorithm design and analysis; Convergence; Finite element methods; Genetic algorithms; Magnetic analysis; Magnetic devices; Response surface methodology; Superconducting magnetic energy storage; Testing;
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2003.810209
