Estimating most productive scale size in DEA with real and integer value data

نویسنده

  • Z. Moghaddas
چکیده

For better guiding a system, senior managers should have accurate information. Using Data Envelopment analysis (DEA) help managers in this objective. Thus, many investigations have been made in order to find the most productive scale size (MPSS) for the evaluating decision making units (DMUs). In this paper we consider this case where there exist subsets of input and output variables to be integer valued. We use data envelopment analysis (DEA) technique, which is a mathematical programming for efficiency evaluation and target setting for a set of DMUs, and develop a model with which the desired MPSS point can be found. The applicability of developed model is illustrated in the context of the analysis to show the validity of the proposed model.

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Estimating most productive scale size in DEA with real and integer value data

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تاریخ انتشار 2014