Developing a multi-objective BCC model in grey environment

Abstract

Data envelopment analysis (DEA) classic models suppose that the data for all inputs and outputs are accurate and determinate and DEA classic model has not defined for inaccurate and indeterminate data. But in the real world, most of the time, there are varieties of uncertainty in the models including interval, fuzzy, grey and probable. In this paper, a DEA multi-objective model is suggested in the grey environment for finding the common weights for decision-making units and computing the privilege of DMUs efficiency for the purpose of more accurate ranking. Finally, in order to assess the results, an example is offered for comparing DMUs ranking via DEA classic models and the presented model.