To find the best sequence of the parts to the production system has been respected by researchers as a research gap especially in robotic cells that are confronted with breakdowns. Through the current study a simulation-based optimization approach is presented to trace the optimum sequence of a two-machine robotic cell that produces different products. A material handling device to support the transport and load/unload in this manufacturing system is a single gripper robot. Here, simulation enables the authors to determine sequencing of parts to the cell; also, a comparison is done based on DEA and DEAGP methods to trace the optimal cyclic sequences satisfying the objective functions, and through Andersen/Petersen's super-efficiency approach, the best cyclic sequence is selected. Applying DEAGP usually improves the discrimination power to select the efficient cyclic sequence of the parts, though the results in this problem are not satisfactory, and DEA results are more reasonable.