Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiencies of decision-making units (DMUs) by using set inputs and outputs. However, traditional DEA models always assume that or outputs are independent each other, which unrealistic in practical problems. To reflect interactions between outputs, Choquet integral employed models. The usually used to find some specif...

The inefficient DMUs are usually arranged after the technical efficient ones by DEA methods, however, it is possible that a technical efficient DMU neither be efficient nor be more efficient than some inefficient ones. This study distinguishes between the terms ‘technical efficiency’ and ‘efficiency’ and demonstrates that the technical efficiency is a necessary condition for being efficient and...

In many managerial applications, situations frequently occur when a fixed cost is used in constructing the common platform of an organization, and needs to be shared by all related entities, or decision making units (DMUs). It is of vital importance to allocate such a cost across DMUs where there is competition for resources. Data envelopment analysis (DEA) has been successfully used in cost an...

The aim of this paper is to evaluate the performance of the faculties of Islamic Azad University of Zahedan Branch based on two-component (teaching and research) decision making units (DMUs) in data envelopment analysis (DEA). Nowadays it is obvious that most of the systems as DMUs do not act as a simple inputoutput structure. Instead, if they have been studied more delicately, they include net...

Data Envelopment Analysis (DEA) is amethodology for evaluating the relative efficiencies of a set of decisionmaking units (DMUs). The original model is based on the assumption that in a multiple input, multiple output setting, all inputs impact all outputs. In many situations, however, this assumption may not apply, such as would be the case in manufacturing environments where some products may...

Ranked voting data arise when voters select and rank more than one candidate with an order of preference. Cook et al.[1] introduced data envelopment analysis (DEA) to analyze ranked voting data. Obata et al.[2] proposed a new method that did not use information obtained from inefficient candidates to discriminate efficient candidates. Liu et al.[3] ranked efficient DMUs on the DEA frontier with...

The traditional data envelopment analysis (DEA) literatures generally concentrated on the efficiency evaluation of single decision making unit (DMU). However, in many practical problems, the decision makers are required to choose a number of DMUs instead of a single one from the DMUs set. Therefore, it is necessary to study the combinatorial efficiency evaluation problem which can be illustrate...

Enterprises typically referred to as decision making units (DMUs) seldom operate in similar environments. Within a relative performance point of view, if DMUs operating in different environments are compared, the units that operate in less desirable environments are at a disadvantage. In order to ensure that the performance comparison is reasonable within an efficiency measurement approach, a t...

Data envelopment analysis (DEA) is a mathematical programming - based technique to evaluate the performance of homogeneous group decision-making units (DMUs) with multiple inputs and outputs. One DEA applications involves aggregating input resources reallocating them create efficient DMUs.The present study employs centralized resource allocation (CRA) approach develop model for creating new DMU...