Abstract:
DEA Classic models cannot be used for inaccurate and indeterminate data, and it is supposed that the data for all inputs and outputs are accurate and determinate. However, in real life situations uncertainty is more common. This article attempts to get the common weights for Decision-Making Units by developing DEA multi-objective models in the grey environment. First, we compute the privilege of DMUs efficiency to receive more accurate ranking. Finally, in order to assess the results, an example is presented to compare the results of the DMUs ranking between DEA Classic models and the presented model.
Machine summary:
This article attempts to get the common weights for Decision-Making Units by developing DEA multi-objective models in the grey environment.
Introduction Data Envelopment Analysis is a powerful managerial technique that provides managers with a device so that they could test the function of their companies against their competitors, and make decision for the better future based on the results (Jafarian-Moghaddam et al.
Generally, in DEA classic model to assess the efficiency of decision making units, the accurate and certain data is used (Charnes et al.
(2012) presented a model of Probable Data Envelopment Analysis in their article that will be obtained by introducing the risk concept and the efficiency of decision-making units (DMU).
Wang and Liu (2012) used a CCR model to solve the DEA with grey interval data while the inputs/outputs have large interval length and found that lengths of efficiency intervals under the hypotheses are shorter, which produces more reliable and informative evaluation results and DMUs are dealt with more fairly.
Therefore we deliberate DEA model of max z 2 s u r y r 2 a r 1 m v i x i 2 i 1 s u r y rn a r 1 multi objective in grey environment to resolve this problem and to obtain logical ranking.