An efficient method for scattering Genetic Algorithm (GA) individuals in the design space is proposed to accelerate airfoil shape optimization. The method used here is based on the variation of the mutation rate for each gene of the chromosomes by taking feedback from the current population. An adaptive method for airfoil shape parameterization is also applied and its impact on the optimum design and convergence of the optimization process isinvestigated. In order to demonstrate the efficiency of the proposed method, a geometric inverse design using Genetic Algorithm is carried out and the capability of the method for producing airfoil shapes is assessed. The performance of the method is further evaluated by an aerodynamic shape optimization. Results indicate the merits of the method in increasing the maximum objective value about7percent as well as decreasing the total computational time up to28 percent.