Abstract. In this paper, the class-shape function transform (CST) parametric method is used to parameterize the airfoil configuration, and a new airfoil is randomly generated within a limited range. The 2D Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) solver is used to compute the quantities such as lift-to-drag ratio. The multi-objective genetic algorithm performs multi-objective optimization design on the airfoil plane shape to achieve high lift-to-drag ratio with low drag in operating ranges of angle of attack, and finally obtains the Pareto optimal solution set. The mixed function of index method is used to increase the thickness of the trailing edge of the airfoil. From the multi-objective solutions and blunt trailing edge solutions which represent the best trade-offs between the design objectives, one can select a set of airfoil shapes with a low relative drag force and with improved aerodynamic performance. Taking a typical airfoil NACA4418 as an example. The results show that the optimized airfoil has a better pressure distribution than the original airfoil, effectively increasing the lift coefficient and reducing the drag coefficient. After thickening the trailing edge of the optimized airfoil, the results show that the lift coefficient is improved at all angles of attack and the stall is delayed. And the blunt trailing edge airfoil has better lift-to-drag characteristics than the original airfoil and the optimized airfoil.