Scale Efficient Targets in Production Systems With Two-stage Structure Under Imprecise Data Assumption

Traditional data envelopment analysis (DEA) models evaluate two-stage decision making unit (DMU) as a black box and neglect the connectivity may exist among the stages. This paper looks inside the system by considering the intermediate activities between the stages where the first stage uses inputs to produce outputs which are the inputs to the second stage along with its own inputs. Additionally, some of the inputs and outputs values may not be completely available because of uncertainty. Data can be interval e.g. when the missing values are replaced by intervals in which the unknown values are likely to belong. We introduce models to optimize two-stage DMU with interval data. Numerical example is applied to clarify the models.