In recent years there has been an exponential growth in the number of publications related
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …

National policy initiatives require the expenditure of large amounts of resources over several
years. It is common for these initiatives to generate large amounts of data that are needed in …

Assessing the efficiency of a supply chain (SC) is of great importance for managers and
policy makers. For this aim, we propose a network data envelopment analysis (NDEA) …

Data envelopment analysis (DEA) is a mathematical programming technique for efficiency
analysis. For dealing with the data in ratio form, the DEA model for ratio data known as DEA …

In this paper we present a new model combining the major underlying ideas behind the
Slacks-Based Measure (SBM) and the Data Envelopment Analysis-Ratio based (DEA-R) …

Purpose This paper aims to present two-stage network models in the presence of stochastic
ratio data. Design/methodology/approach Black-box, free-link and fix-link techniques are …

The data envelopment analysis (DEA) technique is used to identify the strengths and
weaknesses of a set of decision-maker units. In this technique for each decisionmaking unit …

Finding efficient surfaces is quite an important task in data envelopment analysis (DEA)
because scale efficiency, returns to scale, and other characteristics of decision making units …

The present paper proposes a number of models for calculating the average efficiency of
two-stage networks using DEA and DEA-R with fuzzy data. If the input, intermediate, and …

Data envelopment analysis (DEA) is a technique to measure the performance of decision-
making units (DMUs). Conventional DEA treats DMUs as black boxes and the internal …