Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers' intuition and subjective judgements. This ...

Abstract Nowadays among many evaluation methods, data envelopment analysis has widely used to evaluate the relative performance of a set of Decision Making Units (DMUs). Data Envelopment Analysis (DEA(is a mathematical tool for evaluating the relative efficiency of a set Decision Making Units (DMUs), with multiple inputs and outputs. Traditional DEA models treat with each DMU as a “black box" t...

For better guiding a system, senior managers should have accurate information. Using Data Envelopment analysis (DEA) help managers in this objective. Thus, many investigations have been made in order to find the most productive scale size (MPSS) for the evaluating decision making units (DMUs). In this paper we consider this case where there exist subsets of input and output variables to be inte...

abstract. data envelopment analysis (dea) is now widely utilized as a method for assessing relative efficiency of a set of decision making units (dmus). along as evaluating relative efficiency dea models are capable of to be improved for finding benchmark for inefficient units which can help managers for better making decision. thus it is important to obtain accurate results from dea models. in...

In the evaluation of non-efficient units by Data Envelopment Analysis (DEA) referenced Decision Making Units (DMU’s) have an important role. Unfortunately DMU’s with extra ordinary output can lead to a monopoly in a reference set, the fact called abnormality due to the outliers' data. In this paper, we introduce a DEA model for evaluating DMU’s under this circumstance. The layer model can resul...

‎‎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...

The fundamental weakness of a Data Envelopment Analysis (DEA) is its weak discrimination in cases when small number of Decision Making Units (DMU) have been compared. Therefore in such cases the basic DEA model is used in combination with other methods or additional constraints are added to the model. In this paper, the Cross-efficiency method has been combined with the Potential Method (PM).

data envelopment analysis (dea) is a mathematical programming method in operations research that can be used to distinguish between efficient and inefficient decision making units (dmus). however, the conventional dea models do not have the ability to rank the efficient dmus. this article suggests bootstrapping method for ranking measures of technical efficiency as calculated via non-radial mod...