The performance assessment of supply chains including sustainability dimensions of economic, environmental and social is a significant aspect for managers and decision makers. Furthermore, imprecise data are presented in many real world applications. Therefore, the current paper proposes an approach based on data envelopment analysis (DEA) to analyze the revenue efficiency of sustainable supply...

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...

The cross efficiency evaluation is used to performance measurement of decision making units in data envelopment analysis concept. One of the most important shortcoming of this method is existing alternative optimal solution and therefore, the efficiency scores are not unique. We are going to summarize the pervious models proposed by researchers and suggest an alternative secondary goal approach...

One way to rank DMUs in DEA is the cross efficiency method. In this method, the efficiencyof each DMU is calculated by other DMUs optimum weights, which makes the ranking moreacceptable for managers. Existing alternative optimum weights in cross efficiency methodlead to several ranks for DMUs. Several secondary goals have introduced to avoid thisproblem, till now. In this paper, a new model is ...

Data envelopment analysis (DEA) as introduced by Charnes et al [3] is a linear programming technique that has widely been used to evaluate the relative efficiency of a set of homogenous decision making units (DMUs). In many real applications, the input-output variables cannot be precisely measured. This is particularly important in assessing efficiency of DMUs using DEA, since the efficiency sc...

Over a long and remarkably productive career, Professor William W. (Bill) Cooper has made many pioneering contributions to Operations Research and Management Science (OR/MS), with notable forays into the areas of (a) linear and non-linear programming, (b) goal programming, (c) chance-constrained programming, (d) data envelopment analysis, and (e) manpower planning, among others. His legendary p...

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...

Among the various discriminant analysis (DA) methods, researchers have investigated several directions in this area: statistics, econometrics, computer data mining technologies and mathematical programming. Recently, as a nonparametric mathematical programming approach, Data envelopment analysis has been applied in DA area and received great attention. In this paper, we propose a new discrimina...

This paper investigates a procedure for identifying all efficient hyperplanes of production possibility set (PPS). This procedure is based on a method which recommended by Pekka J. Korhonen[8]. He offered using of lexicographic parametric programming method for recognizing all efficient units in data envelopment analysis (DEA). In this paper we can find efficient hyperplanes, via using the para...

in the process of production, some of the inputs are fixed and cannot easily be changed, such as work hours of workers and hours of administrative or work, these types of inputs are fixed and others are variables. in this paper, by considering some inputs or outputs which are limited, their amounts must be integrated; this concept for integer data is extended. we show the importance of subject ...