The Efficiency of MSBM Model with Imprecise Data (Interval)
نویسندگان
چکیده
Data Envelopment Analysis (DEA) is a mathematical programming-based approach for evaluates the relative efficiency of a set of DMUs (Decision Making Units). The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other DMUs in the PPS (Production Possibility Set). Also, in Data Envelopment Analysis various models have been developed in order to evaluate the performance of decision-making units with negative data. The Modified Slack Based Measure (MSBM) model is from collective models family. This modified model is based on slackbased measure (SBM). Also the early models of data envelope analysis considered inputs and outputs as precise data. However, in studies about the data envelope analysis, some methods presented for applying imprecise data. Based on this, data envelope analysis models with interval data have been developed. In this paper, the MSBM model is investigated in presence of interval negative data, and then the efficiency of the model with imprecise data (interval) is evaluated. The efficiency of ten decision-making units is evaluated.
منابع مشابه
The Efficiency of MSBM Model with Imprecise Data (Interval)
Data Envelopment Analysis (DEA) is a mathematical programming-based approach for evaluates the relative efficiency of a set of DMUs (Decision Making Units). The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other DMUs in the PPS (Production Possibility Set). Also, in Data Envelopment Analysis various models have been developed in order to...
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