Magnetic design optimization approach using design of experiments with evolutionary computing

A new optimization method, combining design of experiments with evolutionary computing, is proposed. It handles a set of design variables, the size of which changes during the process. Initially, the most sensitive variables are activated; subsequently, the whole set of variables is activated. The optimal synthesis of a magnetic field for magnetofluid treatment is considered as the case study.