Supplier selections is the kernel mechanism for enhancing the competitiveness of the whole supply chain, and transportation loss is the important issue in the supplier selection problems. Hence, this study addresses the supplier selection problem with considering the transportation uncertainty and assembly sequence. In this study, a robust optimization model is developed to solve supplier selection problem with transportation uncertainty in the multi-echelon supply chain. In addition, a modified genetic algorithm is proposed to solve the robust optimization model. To demonstrate the solving performance of the proposed algorithm, two well known algorithms, Gu-GA and Gu-NSGA, are compared with the proposed algorithm. Finally, the robust price is also analyzed, and we can explore the relationship between robust price and protective level.