‎‎In the Data Envelopment Analysis (DEA) the efficiency of the units‎ ‎can be obtained by identifying the degree of the importance of the‎ ‎criteria (inputs-outputs).In DEA basic models‎, ‎challenges are zero‎ ‎and unequal weights of the criteria when decision‎- ‎making units are‎ ‎evaluated‎. ‎One of the strategies applied to deal with these problems‎ ‎is using common weights of the each input...

Data envelopment analysis provides a theoretical framework for analyzing performance and measuring efficiency. Using data envelopment analysis, we can evaluate units and organizations and discuss about their efficiency or inefficiency. In performance assessment of organizations, the most important goal is to rank the units according to their efficiency. Since ranking decision making units in da...

Interval data envelopment analysis (interval DEA) deals with the problem of efficiency assessment when inputs and/or outputs decision making units (DMUs) are given as interval data. This paper focuses on ranking DMUs First, we define extreme efficient units, super score, best and worst (inefficiency) frontiers in DEA context. Then, propose a novel method based lower upper scores unit under eval...

Data Envelopment Analysis (DEA) cannot provide adequate discrimination among efficient decision making units (DMUs). To discriminate these efficient DMUs is an interesting research subject. The purpose of this paper is to develop the mix integer linear model which was proposed by Foroughi (Foroughi A.A. A new mixed integer linear model for selecting the best decision making units in data envelo...

data envelopment analysis (dea) is a nonparametric approach to estimate relative efficiency of decision making units (dmus). dea and is one of the best quantitative approach and balanced scorecard (bsc) is one of the best qualitative method to measure efficiency of an organization. since simultaneous evaluation of network performance of the quad areas of bsc model is considered as a necessity a...