In this study, both optimistic and pessimistic approaches of data envelopment analysis are applied to propose an equitable ranking method in fuzzy environments. To this end, we suppose that the sum of efficiency scores of all decision making units (DMUs) equals to unity. Using the worst-best and best-worst approaches, the minimum and maximum possible efficiency scores of each DMU are estimated ...

Data envelopment analysis (DEA) is known as a useful tool that produces many efficient decision-making units (DMUs). Traditional DEA provides relative efficient scores and reference sets, but does not influence and rank the efficient DMUs. This paper suggests a method that pro‐ vides influence and ranking information by using Pag‐ eRank as a centrality of Social Network analysis (SNA) based on ...

Data envelopment analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. Crisp input and output data are fundamentally indispensable in traditional DEA evaluation process. However, the input and output data in real-world problems are often imprecise or ambiguous. In this study, we present a four-p...

Data Envelopment Analysis (DEA) is actually to obtain the efficiency using inputs and outputs, which can determine efficient and inefficient units with the help of performance calculations such that the efficiency for efficient DMUs is one and less than one for inefficient DMUs [1]. In some cases, the ranking of the decision-making units are not important for decision-makers, and they are only ...

banks are one of the most important financial sectors in order to the economic development of each country. certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. sometimes the performance of banks must be measured in the presence of undesirable and vague factors. for these reasons in the current paper a procedure based on data envelopment...

data envelopment analysis (dea) is an approach for evaluating performances of decision making units (dmus). the performances of dmus are affected by the amount of sources that dmus used. usually increases in inputs cause increases in outputs. however, there are situations where increases in one or more inputs generate a reduction in one or more outputs. in such situations there is congestion in...

data envelopment analysis (dea) is a branch of management, concerned with evaluating the performances of homogeneous decision making units (dmus). the performances of dmus are affected by the amount of sources that dmus used. usually increases in inputs cause increases in outputs. however, there are situations where increase in one or more inputs generate a reduction in one or more outputs. in ...

In this paper, the performance of [different] units of Water and Sewage Company in Isfahan Province was evaluated using Data Envelopment Analysis (DEA). The purpose of this study was to provide a clear picture of the relative performance of Decision-Making Units (DMUs) in 2018. The advantage of using the DEA model over parametric models is to measure the performance of units using specific weig...

data envelopment analysis (dea) is a non-parametric method for evaluating the relative technical efficiency for each member of a set of peer decision making units (dmus) with multiple inputs and multiple outputs. the original dea models use positive input and output variables that are measured on a ratio scale, but these models do not apply to the variables in which interval scale data can appe...

In this paper, we have developed a heuristic that uses Data Envelopment Analysis (DEA) to rank Decision Making Units (DMUs) with fuzzy input and output values in the order of their probable efficiency. The heuristic is designed to be used with the raw samples of the fuzzy data, and does not require knowledge of the fuzzy data’s probability distribution. It is meant to be a simple method of diff...