data envelopment analysis (dea) models with interval inputs and outputs have been rarely discussed in dea literature. this paper, using the enhanced russell measurement proposes an extended model which permits the presence of interval scale variables which can take both negative and positive values. the model is compared with most well-known dea models of which include the ccr model, the bcc mo...

background improving efficiency of health sector is of particular importance in all countries. to reach this end, it is paramount to measure the efficiency. on the other hand, there are many factors that affect the efficiency of health systems. this study aimed to measure the technical efficiency (te) of health systems in economic cooperation organization (eco) countries during 2004–10 and to d...

Background and Objectives: Evaluating the performance of clinical units is critical for effective management of health settings. Certain assessment of clinical variables for performance analysis is not always possible, calling for use of uncertainty theory. This study aimed to develop and evaluate an integrated independent component analysis-fuzzy-data envelopment analysis approach to accurate ...

this paper introduces discretionary imprecise data in data envelopment analysis (dea) and discusses the efficiency evaluation of decision making units (dmus) with non-discretionary imprecise data. then, suggests a method for evaluation the efficiency of dmus with non-discretionary imprecise data. when some inputs and outputs are imprecise and non-discretionary, the dea model becomes non-linear ...

data envelopment analysis (dea) is one of the scientific method that computes the efficiency by using a powerful mathematics basic. data envelopment analysis is a non-parametric technique to evaluate the efficiency of a set of decision making units (dmu) with multi inputs and outputs . since dea’s models classifies decision making units into two categories of efficient and inefficient, so most ...

supplier evaluation and selection is important in supply chain management. this is a typical multiple criteria decision making that consists of both quantitative and qualitative factors. ahp is a proper approach to aid this decision making problem, because of its inherent capacity to handle qualitative and quantitative criteria, but when criteria are dependent this method is not so good. also t...

while conventional data envelopment analysis models set targets separately for each decision making unit, centralized recourse allocation model is presented where there is a centralized decision maker that supervises all the operating units. optimizing of total input consumption and total output production is the main aim of this model. in this paper, firstly the centralized output production m...