Due to increased individuation of user needs and market globalization, the demands for product performance have diversified. However, a diversified performance is difficult to be obtained a unique design solution (design value). In a previous study, the robust design method (RDM), which ensures products with a robust performance under diverse conditions, was improved. This method was used to evaluate performance robustness with respect to an adjustable control factor (ACF), which is a factor that can be adjusted by the user. Unfortunately, the RDM is not applicable to design problems that have several ACFs due to the increased calculation amount. To resolve this issue, this study improves the previous method by applying a genetic algorithm and a method to extract the values of ACFs employed in the robustness calculation. The improved RDM was applied to two numerical examples to confirm its effectiveness.