Generally, electrical machines are designed using CAE (computer aided engineering) software. In addition, it is combined the design with optimization method for improving various objective functions such as magnetic path, structure and loss. However, there are various problems when multi-objective optimization is applied: modeling of design parameters is complicated, vast amounts of time are necessary, and the result is highly complex display owing to multi-objective. Therefore, it is difficult to select valid value from the complex result. In this paper, the authors have described the method that applies multi-objective function optimization for electrical machine by multi-objective genetic programming (MOGP). Moreover, its superiority and usability have been considered. Likewise, they have described the method that displays the result using dimension reduction.