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...

super eciency data envelopment analysis(dea) model can be used in ranking the performanceof ecient decision making units(dmus). in dea, non-extreme ecient unitshave a super eciency score one and the existing super eciency dea models do notprovide a complete ranking about these units. in this paper, we will propose a methodfor ranking the performance of the extreme and non-extreme ecient u...

in this paper, by introducing two virtual decision-making units (dmus) called ideal dmu (idmu) and anti-ideal dmu (admu) with fuzzy inputs-outputs, the efficiency evaluation of dmus are done by fuzzy data envelopment analysis (fdea). therefore, we evaluate dmus from the perspective of the best and worst possible relative efficiency. for each dmu two efficiencies are calculated while inputs and ...

in models of data envelopment analysis (dea), an optimal set of weights is generally assumed to represent the assessed decision making unit (dmu) in the best light in comparison to all the other dmus, and so there is an optimal set of weights corresponding to each dmu. the present paper, proposes a three stage method to determine one common set of weights for decision making units. then, we use...

Conventional DEA models tend to allocate the fixed resources multiple decision-making units (DMUs) and treat allocated resource as an extra input for every single DMU. However, existing allocation (DEA-RA) methods are applicable exclusively DMUs with exact values of inputs outputs. A lack precision or output data DMUs, such interval data, would cause a failure DMUs. In order resolve this proble...

Ranking decision making units (DMUs) is one of the most important applications of data envelopment analysis (DEA). In this paper, we exploit the power of individual appreciativeness in developing a methodology that combines crossevaluation, preference voting and ordered weighted averaging (OWA). We show that each stage of the proposed methodology enhances discrimination among DMUs while offerin...

in this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (dmus) in stochastic data envelopment analysis (dea) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. it is shown that this deterministic model can be converted to a quadratic programming model. so fa...

Keywords: Data envelopment analysis (DEA) Common weights analysis (CWA) Ranking The ideal line The special line a b s t r a c t Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decision making units (DMUs) in a homogeneous group. However, DEA does not provide more information about the efficient DMUs. In this research, the ...

In many applications, ranking of decision making units (DMUs) is a problematic technical task procedure to decision makers in data envelopment analysis (DEA), especially when there are extremely efficient DMUs. In such cases, many DEA models may usually get the same efficiency score for different DMUs. Hence, there is a growing interest in ranking techniques yet. The purpose of this paper is ra...

One of the difficulties of Data Envelopment Analysis(DEA) is the problem of de_ciency discrimination among efficient Decision Making Units (DMUs) and hence, yielding large number of DMUs as efficient ones. The main purpose of this paper is to overcome this inability. One of the methods for ranking efficient DMUs is minimizing the Coefficient of Variation (CV) for inputs-outputs weights. In this...