The parallel network dynamic DEA model with interval data

In original DEA models, data apply precisely for measuring the relative efficiency whereas in reality, we do not always deal with precise data, also, be noted that when data are non-precision, it is expected to attain non-precision efficiency due to these data. In this article, we apply the parallel network dynamic DEA model for non-precision data in which the carry-overs among periods are assumed as desired and undesired. Then Upper and lower efficiency bounds are obtained for overall-, periodical-, divisional and periodical efficiencies the part which is computed considering the subunits of DMU under evaluation. Finally, having exerted this model on data set of branches of several banks in Iran, we compute the efficiency interval.