A Novel Taguchi-Simulated Annealing Method and its Application to Airfoil Design Optimization

Abstract

Listen

Translate article

A classical simulated annealing (SA) method uses a stochastic process based on probability, rather than a deterministic procedure, to seek the minima or maxima in the solution space. Although the classical SA method can find the optimal solution for most linear and nonlinear optimization problems, the algorithm requires numerous numerical iterations, resulting in computational inefficiencies. The proposed method also frequently fails to achieve optimal solutions to large parameter optimization problems. Therefore, this study incorporates well-known Taguchi orthogonal arrays, which involve fractional factorials based on orthogonal tables, with the classical SA to enhance the numerical convergence and accuracy of the optimal solution. The novel combination of the classical SA and Taguchi orthogonal arrays is termed the Taguchi-SA herein. The performance of the proposed Taguchi-SA method is evaluated by computing several representative global optimization problems, such as a multi-modal function and large parameter optimization problems. The numerical results show that the proposed Taguchi-SA method markedly outperforms the classical SA in solving global optimization problems. Additionally, the proposed method is applied to an airfoil design optimization to examine the effectiveness of the Taguchi-SA method in practical aerodynamic optimization design. The objective function of the airfoil design is to minimize the pitching-down moment. The pressure distribution results and aerodynamic data, such as lift, drag and pitching moment coefficients, clearly indicate that the aerodynamic performance of the present airfoil is better than that of the original. Accordingly, the computational results show that the proposed Taguchi-SA method is efficient and robust in determining the optimal design variables and the objective function value.