This paper proposes a method for ranking decision making units (DMUs) using some of the multiple criteria decision making / multiple attribute decision making          (MCDM /MADM) techniques, namely, interval analytic hierarchy process (IAHP)          and the technique for order preference by similarity to an ideal solution (TOPSIS).          Since the efficiency score of unity is assigned to ...

This study uses the data envelopment analysis (DEA) to assess the progress/regression of decision-making units (DMUs) having a two-stage structure‎. ‎The progress/regression of these DMU can be assessed in the first stage‎, ‎the second stage‎, ‎and the whole system‎. ‎In the first stage‎, ‎the progress/regression of bank branches in collecting resources and in the second stage their progress/re...

This paper presents a data envelopment analysis (DEA) model combined with Bootstrapping to assess performance of one of the Data mining Algorithms. We applied a two-step process for performance productivity analysis of insurance branches within a case study. First, using a DEA model, the study analyzes the productivity of eighteen decision-making units (DMUs). Using a Malmquist index, DEA deter...

Today, one of the most fundamental issues within the field of industrial and nonindustrial activities is evaluate the costs performance of the units which are associated with industrial and nonindustrial activities. Data envelopment analysis (DEA) is a nonparametric method for evaluating performance. Fuzzy sets theory is a powerful tool for mentioning ambiguous situations. Traditional DEA model...

Data envelopment analysis (DEA) is a mathematical method to evaluate the performance of decision-making units (DMU). In the performance evaluation of an organization based on the classical theory of DEA, input and output data are assumed to be deterministic, while in the real world, the observed values of the inputs and outputs data are mainly fuzzy and random. A normal distribution is a contin...

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 ...

The traditional data envelopment analysis (DEA) models treat a decision making unit (DMU) as a “black box”, which is often criticized for not considering the inner production mechanism of a production system. The network DEA models developed to overcome this deficiency by considering the internal structure of a DMU have recently gained popularity. The inner data, however, are not generally avai...

Data Envelopment Analysis (DEA) as a non-parametric method for efficiency measurement allows decision making units (DMUs) to select the most advantageous weight factors in order to maximize their efficiency scores.  In most practical applications of DEA presented in the literature, the presented models assume that all inputs are fully desirable. However, in many real situations undesirable inpu...

Bankruptcy in the same amount of time and history is very rampant and therefore the vision of the future can be prevented. Using data envelopment analysis (DEA) and malmquist index can precise evaluating of the performances of many different kinds of decision making units (DMU) such as hospitals, universities, business firms, etc. In this paper, we will modify directional distance formulation o...

The full ranking or complete ranking of decision making units is one of the main ‎issues in data envelopment analysis. A full ranking is a ranking that considers all ‎efficient and inefficient units simultaneously and finds a ranking for them. Almost all ‎of the developed ranking methods consider only the efficient units. On the other hand, ‎ranking inefficient units by traditional data envelop...