This paper presents a novel approach to achieving the goals of data envelopment analysis in the process of reconstruction and integration of decision-making units by using multiple objective linear programming. In this regard, first, we review inverse data envelopment analysis models for data reconstruction and integration. We present a model with multi-objective linear programming structure in inverse data envelopment analysis. The superiority of the model to prioritize inputs and outputs in the input and output data integration process. Finally, we used of bank data for showing the validity of proposed approach and we proposed results. پرونده مقاله

One of the problems of the data envelopment analysis traditional models in the multiple form that is the weights corresponding to certain inputs and outputs are considered zero in the calculation of efficiency and this means that not all input and output components are utilized for the evaluation of efficiency, as some are ignored. The above issue causes the efficiency score of the under evaluation unit not to be calculated correctly. One of the ways to deal with the pseudo-inefficiency is to use data envelopment analysis models with multi-criteria structure. In this regard, we first investigate the models of data envelopment analysis with multi-criteria structure and further, with regard to the ability of the ratio-based data envelopment analysis models, we develop data envelopment analysis models with a multi-criteria structure for ratio data and the feasibility and the bounded condition of the above models and their efficiency intervals are described. By presenting a numerical example, we compare the efficiency scores obtained from the models presented with the previous models and we show that the proposed models can be used to deal with the pseudo-inefficiency and efficiency underestimation. Finally, we present the results. پرونده مقاله

This study presents a reasonable program for large commercial banks in order to supply bank resources by the long term bank deposits and investments, making balance between financial commitments and investments, enhancing the value at risk by maintaining market and bank high liquidity, management of crisis in condition of liquidity shortage and funds, assessment of value at risk index by using determination bank interval efficiency, ranking the set of commercial big bank by using of the fuzzy data envelopment analysis (DEA) models. In the following, we extend fuzzy slack-based model (SBM) for fuzzy inputs and outputs data. We are determined the risk factors in bank operating process by using of inefficiency concept. In this study, we use the data of seven banks which were accepted in Tehran Stock Exchange (Eghtesad novin bank, Parsian, Tejarat, Sina, Karafarin, Melat and Saderat) over a 4 years' period from 2012 to 2015. We use the fuzzy DEA for assessment of value at risk index for Banks listed on the Tehran Stock Exchange. پرونده مقاله