Optimal Design of Brushless DC Motor Using Parallel Genetic Algorithm

Optimal Design of Brushless DC Motor Using Parallel Genetic Algorithm

The optimization problems that have many design variables, such as the design of brushless DC motor (BLDCM), the conventional genetic algorithms fall into a trap of local minima with high probability. Parallel genetic algorithms are one of the most famous spatial separation algorithms to avoid it. Parallel genetic algorithms maintain multiple and separate subpopulations which are linked by the genetic operation of migration. The migration mechanism consists of several parameters such as the migration size, the migration interval, and the migration topology. In this paper, we propose a new method about the migration interval. To verify its validity, this method is applied to some traditional mathematical problems.