Sensitivity Analysis in Data Envelopment Analysis for Interval Data

Abstract

Data Envelopment Analysis (DEA) analysis model can evaluate the relative efficiency of a set of DMU decision-making units with the right values but cannot handle data that is not correct, for example data in the form of intervals. In this paper, the DEA model is able to calculate the data efficiency of interval values. Data Envelopment Analysis interval or DEA interval is an approach that can make input and output data from Data Envelopment Analysis which is used to measure the relative efficiency of Decision Making Unit (DMU) in multi input and multi output processes which will be examined in this study. This model is based on arithmetic operations with interval numbers not the same as the DEA model in general that uses single data. Measurement of the relative efficiency of DMUs with inputs and outputs that have interval data using a constant interval of interval, depending on the application, can also be estimated using statistical techniques or experience. Because in the world most data is interval data, we present a model to calculate the lower and upper limits for each DMU and prove that this model provides higher and lower efficiency limits. In this paper the number of DMUs is increased where if one DMU is added then all highly efficient units will remain.