Abstract
Magnetic shielding and shunting in industrial devices is crucial for keeping stray losses and hot-spot appearances as low as possible. Nevertheless, the additional costs for magnetic shunts and conductive shields have to be taken into account. Therefore, an optimal trade-off between a remarkable reduction of the stray losses and the design and position of the shielding devices has to be found. A higher order evolution strategy is applied to perform this task. The relevant objectives are merged into a single number by applying a fuzzy membership function to each objective, respectively. These membership functions can be implemented as static ones or in a way, that they adjust themselves dynamically during the optimization process. In general multi-objective problems show a number of local solutions besides the global one and it is worth to investigate as many of the local solutions as possible as well. Therefore, a most desirable behaviour would be if the optimization strategy behaves globally and yields additional information about local minima detected on the way to the global solution. This goal can be achieved by clustering the population prior to the recombination process and by performing the recombination in a cluster sensitive way.