application of inverse data envelopment analysis models to preserve mpss

One of the most important aspects in data envelopment analysis (dea) is the returns to scale and most productive scale size (mpss). the new model is introduced here based on inverse data envelopment analysis for preserving mpss when data are changed. in this method, we determine the mpss decision-making units (dmus); then, for each one of them, the outputs are increased and the values of the required increment of inputs are obtained, while the unit under evaluation remains mpss. the applicability of the developed model illustrates through some numerical examples to show the validity of the proposed model