Wing design using real-coded adaptive range genetic algorithm

Abstract

Real-coded adaptive range genetic algorithms (ARGAs) have been developed. The real-coded ARGAs possess both advantages of the binary-coded ARGAs and the use of the floating point representation to overcome the problems of having a large search space that requires continuous sampling. First, the efficiency and the robustness of the proposed approach have been demonstrated by using a typical test function. Then the proposed approach has been applied to an aerodynamic airfoil shape optimization problem. The results confirm that the real-coded ARGAs consistently find better solutions than the conventional real-coded GAs do. The design result is considered to be the global optimal and thus ensures the feasibility of the real-coded ARGAs in aerodynamic designs.