Real-coded Adaptive Range Genetic Algorithm and its application to aerodynamic design

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 are demonstrated by test functions. Then the proposed approach is 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 Genetic Algorithms do. The designed airfoil shape is considered to be the global optimal and thus ensures the feasibility of the real-coded ARGAs in aerodynamic designs.