Genetic Algorithm is a probability based optimization method using the evolutionary patterns of the nature. The convenience of the use and the diversification of the application make GA one of the useful optimization methods. But some demerits such as slow convergence and instability of the solution restrict the GA`s applicable limits. To overcome these limitations, hybrid genetic algorithm is constructed which combined a few ideas of direct optimization methods such as local search, simulated annealing, etc. Using this GA, 2 dimensional wing shape optimizations are performed. The aerodynamic optimizations - drag minimization - about Euler and Navier-Stokes equations and the aerodynamic and electromagnetic coupled optimization - drag and RCS(radar Cross Section) minimization - about Euler and Navier-Stokes at the aerodynamic analysis and high frequency region at the electromagnetic analysis are fulfilled. As shape functions for wing shape generation methods, Hicks-Henne functions and NURBS are used and then compared the optimization results according to the ability of the shape representation. For this study, more extended application of genetic algorithms compared with previous studies in Aerospace Engineering are the main concept.
