Journal of Operational Research and Its Applications ( Applied Mathematics ) - Lahijan Azad University

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Data Envelopment Analysis (DEA) is based on a mathematical programming method to evaluate the performance of decision-making units (DMUs) with multiple inputs and outputs. In DEA, input and output weights can take any non-negative value to achieve the best performance. One of the problems with this type of evaluation is the low discriminate of these models. Weight reduction methods have been introduced as a solution to this problem and improve the discrimination of DEA models. The purpose of this paper is to present a data envelopment analysis model with a new weight reduction. The constraint presented using the mean and standard deviation of variable weights is related to efficient DMUs. Considering the variable weights is due to the non-unique weights obtained in the multiplier model. The proposed model is also used to evaluate the efficiency of bank branches in Iran. We will use this method to evaluate the efficiency of 40 branches of a commercial bank in Iran for two consecutive years. The results of the model implementation show that the discrimination of DMUs is increased  using the proposed model and the results confirm the theoretical points expressed about the proposed method.

Keywords: Data Envelopment Analysis, Restricted Weights, Efficient Faces, Evaluating the Efficiency of Bank.

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