Application of vector optimization employing modified genetic algorithm to permanent magnet motor design

This paper presents a method to solve the vector optimization problem that determines both the noninferior solution set and the best compromise solution employing a modified genetic algorithm. The algorithm differs from the conventional one in the definition of fitness value and convergence criterion. Some parameters of the algorithm are adjusted to the vector optimization. The algorithm also contains the additional routine for searching the best compromise solution. This method is applied to the optimal design of the permanent magnet synchronous motor for which two objective functions regarding motor efficiency and weight are used.