This article developed an approached model of congestion, based on relaxed combination of inputs, in stochastic data envelopment analysis (SDEA) with chance constrained programming approaches. Classic data envelopment analysis models with deterministic data have been used by many authors to identify congestion and estimate its levels; however, data envelopment analysis with stochastic data were...

The purpose of this paper is to investigate the levels of technical efficiency in agricultural sector of MENA countries by using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) approaches in 2007-2008. The results show that the total average of technical efficiency is as follows: DEABCC(0.770)>DEACCR(0.744)>SFA(0.479), and among all MENA countries, the best performanc...

More than 200 papers have been published in the last 20 years on the topic of health supply chains (HSC). Looking at the research methodologies employed, less than 15 papers apply data envelopment analysis (DEA) models. This is in contrast to, for example, A Network Data Envelopment Analysis (NDEA) Model for Supply Chain Performance Evaluation where several reviews on respective NDEA models hav...

for efficiency evaluation of some of the decision making units that have uncertain information, rough data envelopment analysis technique is used, which is derived from rough set theorem and data envelopment analysis (dea). in some situations rough data alter nonradially. to this end, this paper proposes additive rough–dea model and illustrates the proposed model by a numerical example.

Stochastic nonparametric envelopment of data (StoNED) combines the virtues of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) into a unified framework of frontier estimation. StoNED melds the nonparametric piece-wise linear DEA-type frontier with stochastic SFA-type inefficiency and noise terms. We show that the StoNED model can be estimated in the panel data setting in a...

Supplier selection has a strategic importance for every company. Hybrid integer data is one of the models in data envelopment analysis (DEA). In many real world applications, data are often stochastic. A successful approach to address uncertainty in data is to replace deterministic data via random variables, leading to chance-constrained DEA. In this paper, a chance-constrained hybrid integer d...

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...

Recent research has shown that combination approaches, such as taking the maximum or mean over different methods of estimating efficiency scores, have practical merits and offer a useful alternative to adopting only one technique. This recent shows minimizes risk underestimation, improves precision estimation. In this paper, we propose implement formal criterion weighting based on maximizing pr...