Data Envelopment Analysis (DEA) is the most popular mathematical approach to assess efficiency of decision-making units (DMUs). In complex organizations, DMUs face a heterogeneous condition regarding environmental factors which affect their efficiencies. When there are large number objects, non-homogeneity significantly influences scores that leads unfair ranking DMUs. The aim this study deal w...

data envelopment analysis (dea) is a technique based on mathematical programming for evaluating the efficiency of homogeneous decision making units (dmus). in this technique, inefficient dmus are projected onto the frontier, which was constructed by the best performers. centralized resource allocation (cra) is a method in which all dmus are projected onto the efficient frontier through solving ...

envelopment analysis (dea) is a very eective method to evaluate the relative eciency of decision-making units (dmus). dea models divided all dmus in two categories: ecient and inecientdmus, and don't able to discriminant between ecient dmus. on the other hand, the observedvalues of the input and output data in real-life problems are sometimes imprecise or vague, suchas interval data, ...

data envelopment analysis operates as a tool for appraising the relative efficiency of a set of homogenous decision making units. this methodology is applied widely in different contexts. regarding to its logic, dea allows each dmu to take its optimal weight in comparison with other dmus while a similar condition is considered for other units. this feature is a bilabial characteristic which opt...

The highest efficiency score 1 (100% efficiency) is regarded as a common benchmark for Decision Making Units (DMUs). This brings about the existence of more than one DMU with the highest score. Such a case normally occurs in all Data Envelopment Analysis (DEA) models and also in all the Common Set of Weights (CSWs) methods and it may lead to the lack of thorough ranking of DMUs. And ideal DMU b...

In view of multi-attribute decision-making problems with interval numbers in social economy and engineering system, this paper defines and analyzes the basic operational rule, normalized method, sequence comparison strategy, and the calculating formula for the distance of interval numbers and interval number sequence. It presents weighted TOPSIS decision-making model based on interval numbers o...

DMUs under DEA evaluation are assumed to be homogeneous. That means the units should undertake similar activities, use common technologies, and operate in similar environments. If one of these assumptions is violated, the efficiency estimates of these DMUs will be biased. This paper firstly analyzes the impacts of DMUs’ non-homogeneity caused by technology difference on the efficiency estimates...

Data envelopment analysis (DEA) is a non-parametric approach for measuring the efficiency of decision making units (DMUs) that use multiple inputs in order to produce multiple outputs. In most real applications, DMUs have a two-stage network process which can be used for management of organizations such as hospitals, insurance companies, banks, and etc. The data are crisp in the standard DEA mo...