A New Method for Ranking Distribution Companies with Several Scenarios Data by Using DEA/MADM

In Data Envelopment Analysis, uncertain data are the inseparable part of real models. Natural models usually deal with uncertain and probable data. Many researchers prioritize these kinds of data. For instance, they study fuzzy data, interval data, probabilistic models etc. In this article, we proposed a method in which the decision making units are uncertain in their inputs and outputs. In the proposed method, it is supposed that the inputs and outputs have different scenarios with specific probability occurrence. In this article, applying VIKOR technique rather than point estimate, the decision making units whose inputs and outputs have different scenarios with specific probability occurrence are ranked. It finds the compromise ranking list and the compromise solution obtained with the given weights from a set of alternatives in the presence of conflicting criteria. In this article, we combine the DEA and the VIKOR method to rank DMUs with different scenarios with a specified probability for input and output data. To illustrate the ability of proposed combined method, a numerical example of 38 Iranian electricity distribution companies is considered.