An engineering design needs many trade-off studies and an analysis for interrelationship among design parameters to simultaneously fulfil various requirements. Further, in modern aircraft designs, the multi-objective optimization problem is emerged to meet the maximum lift, lift-to-drag ratio and others. Moreover a parameter-based investigation for performance improvement is essential to satisfy further requirements. As this purpose, the Adaptive Range Multi-Objective Genetic Algorithm code was developed, and an interrelationship among design parameters Is analyzed using the Self-Organizing Map. In order to achieve the better maximum lift and lift-to-drag ratio than reference airfoil at landing and cruise conditions, maximum lift coefficient and lift-to-drag ratio were chosen as object functions. Furthermore, the PARSEC method reflecting geometrical properties of airfoil was adopted to generate airfoil shapes. Finally, two airfoils, which show better aerodynamic performance that a reference airfoil, were chosen. as a result, maximum lift coefficient and lift-to-drag ratio were increased of 3.32% and 2.26% for first candidate airfoil and 2.48% and 1.69% for second candidate airfoil. Also interrelationship among design parameters for all candidates is analyzed using the Self-Organizing Map.