Data Envelopment Analysis, DEA
Z. Taeb; F. Hosseinzadeh Lotfi; S. Abbasbandy
Abstract
In the last years, several techniques have been reported for managing a system and recognition of the related decision making units. One of them is based on mathematical modeling. Efficiency of any system is very important for all decision makings. Often applied data have time dependent inputs/ outputs. ...
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In the last years, several techniques have been reported for managing a system and recognition of the related decision making units. One of them is based on mathematical modeling. Efficiency of any system is very important for all decision makings. Often applied data have time dependent inputs/ outputs. To calculate the efficiency of time dependent data, a new calculation method has been developed and reported here. By this method, the efficiency has been calculated, with minimum errors and minimum mathematical solving model. The data are often time dependent, therefore Spline function has been estimated as a function of time, without using any particular time. Based on this developed function, the efficiency of time dependent data of a numerical example has been calculated and reported.
Data Envelopment Analysis, DEA
M. Nayebi; F Hosseinzadeh Lotfi
Abstract
The science of Data Envelopment Analysis (DEA) evaluates the effectiveness of decision making units. But, one of the problems of Data Envelopment Analysis (DEA) is that, if the number of units with the same efficiency equal to one was more than one, then we couldn’t select the best between them. ...
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The science of Data Envelopment Analysis (DEA) evaluates the effectiveness of decision making units. But, one of the problems of Data Envelopment Analysis (DEA) is that, if the number of units with the same efficiency equal to one was more than one, then we couldn’t select the best between them. It means that, we can’t rank them. Therefore, the need for ranking these units is considered by the managers. Different methods were proposed in this context. Most of these methods are modeled by DEA models. Due to the variety of ranking methods in DEA, this paper will describe ranking methods which are based on super-efficiency. More precisely, we introduced methods that rank using elimination (removing) of decision making units under the evaluation of observations(set). These methods have some advantages and disadvantages such as, model feasibility or infeasibility, stability or instability, being linear or nonlinear, being radial or non-radial, existence or non- existence of bounded optimal solution in objective function, existence or non- existence of multiple optimal solution, non-extreme efficient units ranking, complexity or simplicity of computational processes, that in this paper, Super Efficiency methods are compared with these eight properties.
Data Envelopment Analysis, DEA
F Hosseinzadeh Lotfi; M. Jahanbakhsh
Abstract
By distinction between efficiency and effectiveness scales, the aim of this paper is to propose a model that can show the differents of efficiency and effectiveness. For this purpose, enveloping form of ICCR model ,has considered to calculate simultaneously the influences of efficiency and effectiveness. ...
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By distinction between efficiency and effectiveness scales, the aim of this paper is to propose a model that can show the differents of efficiency and effectiveness. For this purpose, enveloping form of ICCR model ,has considered to calculate simultaneously the influences of efficiency and effectiveness. this model, is a linear programming model based on Data envelopment analysis (DEA), that combine the input and output oriented CCR model to investigate the efficiency and effectiveness impressed each other ,in a three-stage process. By applying the model on data of 24 bank branches, the result clarify comprehensive view of the performance of the branches that have been substantially three-stage.
F Hosseinzadeh Lotfi; M. Piri
Volume 3, Issue 3 , September 2014, , Pages 69-74
Abstract
Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of Decision Making Units (DMUs) which was first introduced by Charnes, Cooper and Rhodes in1978 as the CCR model .One of the most important topics in management science is determining the efficiency of DMUs. DEA technique ...
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Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of Decision Making Units (DMUs) which was first introduced by Charnes, Cooper and Rhodes in1978 as the CCR model .One of the most important topics in management science is determining the efficiency of DMUs. DEA technique is employed for this purpose. In many DEA models, the best performance of a DMU is indicated by an efficiency score of one. There is often more than one DMU with this efficiency score. To rank and compare efficient units, many methods have been introduced. Moreover, the main assumption in all DEA models was that all input and output values are positive, but practically, we encounter many cases that violate this term and we ultimately have negative inputs and outputs.
F. Piran; F Hosseinzadeh Lotfi; M. Rostami-Malkhalifeh
Volume 2, Issue 4 , December 2013, , Pages 15-25
Abstract
Data envelopment analysis (DEA) is a non-parametric analytical methodology widely used in efficiency measurement of decision making units (DMUs). Conventionally, after identifying the efficient frontier, each DMU is compared to this frontier and classified as efficient or inefficient. This thesis introduces ...
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Data envelopment analysis (DEA) is a non-parametric analytical methodology widely used in efficiency measurement of decision making units (DMUs). Conventionally, after identifying the efficient frontier, each DMU is compared to this frontier and classified as efficient or inefficient. This thesis introduces the most productive scale size (MPSS), and anti- most productive scale size (AMPSS), and proposes several models to calculate various distances between DMUs and both frontiers. Specifically, the distances considered in this paper include: (1) both the distance to MPSS and the distance to AMPSS, where the former reveals a unit’s potential opportunity to become a best performer while the latter reveals its potential risk to become a worst performer, and (2) both the closest distance and the farthest distance to frontiers, which may proved different valuable benchmarking information for units. Subsequently, based on these distances, eight efficiency indices are introduced to rank DMUs. Due to different distances adopted in these indices, the efficiency of units can be evaluated from diverse perspectives with different indices employed. In addition, all units can be fully ranked by these indices.
F. Hosseinzadeh Lotfi; G.R. Jahanshahloo; S. Hemati; S. Givehchi
Volume 1, Issue 2 , July 2012, , Pages 27-39
Abstract
Data envelopment analysis (DEA) mainly utilizes envelopment technology to replace production function in microeconomics. Based on this replacement, DEA is a widely used mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. Evaluating ...
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Data envelopment analysis (DEA) mainly utilizes envelopment technology to replace production function in microeconomics. Based on this replacement, DEA is a widely used mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. Evaluating the efficiency of DMUs that have two-stage network structures is so important in management and control. The resulting two stage DEA model not only provides an overall efficiency score for the entire process, but also yields an efficiency score for each of the individual stages. In this Paper we develops Nash bargaining game model to measure the performance of DMUs that have a two-stage structure. Under Nash bargaining theory, the two stages are viewed as players. It is shown that when only one intermediate measure exists between the two stages, our newly developed Nash bargaining game approach yields the same results as applying the standard DEA approach to each stage separately. With a new breakdown point, the new model is obtained which by providing example, the results of these models are investigated. Among these results can be pointed to the changing efficiency by changing the breakdown point.