Today, evolutionary type of algorithms is entering in many engineering fields. This technique is required to create a population; once the population is created new members are obtained by modifying the previous ones. Recent development in the computer technology and numerical algorithms let the researchers develop fast and powerful ways plugging the evolutionary type algorithms by which several parameters can be determined considering and satisfying many requirements simultaneously to find an optimum solution, i.e. a design fulfilling all requirements including in the fitness function in the design of aerodynamic shaped objects such as wing sections, airfoils, turbine blades or other lift producing surfaces. The time consuming flow solvers and gradient type optimization techniques have not been preferred recently. Instead of this, flow solvers are carried into parallel computing type machines and optimizations are carried out by evolutionary techniques. In this study, Onera M6 wing has been optimized on two parameters, the wing section and the taper ratio by combining recent preferable approach i.e. parallel computing and evolutionary techniques. The dynamic mesh technique has been applied, for the first time, to determine the mesh structures of genetically obtained new members in the genetic algorithms. The Vibrational Genetic Algorithm is applied to 3-D wing optimization problems. To overcome some problems encountered in 3-D applications, such as large calculation time, flow solution difficulties, force calculations; some techniques like parallelization, purification and finite element numeric integration are employed, developed and adapted to this research. The code developed for this aim is robust and faster than the codes, which are only producing mesh by classical techniques. The flow solver ACER3D has been used to obtain the flow parameters for each member. Because the operating time of the program is very long, parallel processing has been used. The Vibrational Genetic Algorithm (VGA) is a GA, which uses the vibration concept, in that, by applying a vibrational mutation periodically to all individuals in a population; they are spread out over the design space. Therefore, it becomes possible to escape from local optimums and thus to obtain a global optimum quickly. This vibration strategy in the mutation is used after a recombination. The unstructured tetrahedral mesh is modified according to the change in wing sections by using dynamic mesh technique and for all members of a generation; new mesh structures have been calculated. Aerodynamic force, lift and drag, calculations have been done by using a finite element method. The pressure value for each triangular wall boundary face is taken as the average of the pressures on the corner nodes. Then the total forces are calculated by using a numerical integration. In the optimization process, there are 14 members in each generation. These are 14 Onera M6 wing planforms that have different wing sections. All of them are solved by ACER3D and their lift and drag forces are calculated. The best member is kept in each generation and carried into the next generation. So the best member found in each generation cannot be worse than the best member of the previous generation. The CPU time of the first step in dynamic mesh method is approximately the same as the mesh generation time. However, at the later steps of dynamic mesh technique much less time is needed than the first step. Therefore, especially, if a lot of configurations are to be considered, the dynamic mesh method offers more advantage. From the results, it is observed that the optimization process is working as expected. The drag coefficient was reduced by about 25 percent. While this has been done, its lift coefficient is tried to be close to the design value determined at the beginning. This is done by arranging the fitness function. At the 30th generation, the difference between the lift coefficient of the best member and the design lift coefficient value is about 1 percent and the difference between thickness ratios is 3 percent. The taper ratio is getting smaller while the code is trying to minimize the drag force. But it cannot be reduced to very small values and is kept almost the same at the later steps, because the program should not only reduce the drag force but also hold the lift force close to the design value.