نتایج جستجو برای: Performance, Reference Units, Weights
تعداد نتایج: 1478921 فیلتر نتایج به سال:
data envelopment analysis (dea) was developed to help compare the relative performance of decision-making units. it is a non-parametric method for performing frontier analysis. it uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics [3]. dea generates an efficiency score between 0 and 1 for each unit...
Data Envelopment Analysis (DEA) was developed to help compare the relative performance of decision-making units. It is a non-parametric method for performing frontier analysis. It uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics [3]. DEA generates an efficiency score between 0 and 1 for each unit...
data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...
In this paper, the performance of [different] units of Water and Sewage Company in Isfahan Province was evaluated using Data Envelopment Analysis (DEA). The purpose of this study was to provide a clear picture of the relative performance of Decision-Making Units (DMUs) in 2018. The advantage of using the DEA model over parametric models is to measure the performance of units using specific weig...
Data envelopment analysis (DEA) does not provide more information about the efficient decision making units (DMUs). A method to rank efficient DMUs is common set of weights (CSW). This research proposes some simple methods to find common set of weights CSW for the performance indices of DEA efficient DMUs. These methods use the results of the standard DEA models to determine the CSW. Unlike the...
Data envelopment analysis (DEA) is non-parametric linear programming (LP) based technique for estimating the relative efficiency of different decision making units (DMUs) assessing the homogeneous type of multiple-inputs and multiple-outputs. The procedure does not require a priori knowledge of weights, while the main concern of this non-parametric technique is to estimate the optimal weights o...
an adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. another key feature of this structure is the fact that, it does not need model of the system. in this scheme, neurolinearizer has few weights, so it is practical in adaptive situations. online training of neurolinearizer is compared to model predictive recurrent training...
A New Robust Bootstrap Algorithm for the Assessment of Common Set of Weights in Performance Analysis
The performance of the units is defined as the ratio of the weighted sum of outputs to the weighted sum of inputs. These weights can be determined by data envelopment analysis (DEA) models. The inputs and outputs of the related (Decision Making Unit) DMU are assessed by a set of the weights obtained via DEA for each DMU. In addition, the weights are not generally common, but rather, they are ve...
Data envelopment analysis (DEA) estimates the relative performance of decision making units (DMUs). This paper uses the idea of the Analytical hierarchy process (AHP) method and fuzzy set theory to modify the model of DEA which can be used to evaluate the performance of business units. In this paper, a new method has been proposed for estimating the performance of DMUs with interval data an...
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