Aircraft design is an extremely complex and multi-disciplinary process. On the designer point of view, it is very difficult to establish the influence of all first-line variables even in earlier phases of the design. The conventional methods of optimization are limited by numbers and types of the considered parameters, as well as by the characteristics of the problem itself, resulting in sub-optimum solutions. In conceptual studies, the determination of configuration variables to satisfy a series of mission requirements is a major and natural field for multi-disciplinary (MDO). The main goal of this work was the development of an optimal design framework running under MATLAB for aircraft conceptual design. Considering the robustness of genetic algorithm to handle a broad class of optimization problems, the use of genetic algorithms is suitable to the treatment of non-linear problems and also of problems with variables of discrete type is possible. In addition, tradeoffs exist among the various objectives of an optimization task and evolutionary algorithms possess many attractive advantages to solve the multi-objective problem. For these reasons, the framework under consideration makes use of a multi-objective genetic algorithm. The multi-disciplinary approach enables that the disciplines of aerodynamics, loads, structures, propulsion, handling qualities, cost estimation, and stability and control can interact in a balanced way, providing a realistic aircraft configuration to be worked further.