Modified differential evolutionary algorithm for fast simulation optimization and its application

A modified differential evolutionary algorithm(MDE) is proposed. MDE adopts "Position" varying scale factor, which calculates the scale factor linearly according to the position of each individual after arranging by the fitness. To maintain good diversity, normal distribution function is used to disturb the parameters of MDE. A new mutation operator is proposed too, which can enhance the exploration efficiency and precision associating with basic mutation operator. The benchmark function result shows that the algorithm not only has good performance of exploration precision, but also has faster convergence speed than basic DE. At last, MDE is applied in aerodynamic optimization of turbine in LRE, and the result shows aerodynamic efficiency is increased by 2.5% with low computational cost. The application instance indicates good applicability of MDE for simulation optimization problem.