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

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.