Data Envelopment Analysis, DEA
Mehdi Soltanifar
Abstract
Linear Assignment (LAM) is one of the Multi-Attribute Decision Making (MADM) methods that uses integer programming models in the solution process. In this method, only the final priority of the alternatives is determined and the distance between the alternatives is not clear. The purpose of this paper ...
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Linear Assignment (LAM) is one of the Multi-Attribute Decision Making (MADM) methods that uses integer programming models in the solution process. In this method, only the final priority of the alternatives is determined and the distance between the alternatives is not clear. The purpose of this paper is to modify this method so that instead of the final priority of the alternatives, the final weight of the alternatives is presented. This is done using a linear programming model of Data Envelopment Analysis (DEA). In this paper, we propose a hybrid MADM-DEA method called Linear Assignment Voting (VLAM). The new method is explained with a numerical example. The method will then be implemented on a problem in the real world to demonstrate the application of the method. In this case study, VLAM demonstrates the prioritization of models proposed by experts for the purchase of excavators in a road construction company. Also, based on the results of this method, the weight of the first, second and third priorities are 0.39, 0.35 and 0.26, respectively. These results increase the decision maker's power in making the final decision and choice.
Data Envelopment Analysis, DEA
Mahnaz Maghbouli; Fatemeh Moradi
Abstract
Emotional Intelligence (EQ) is considered as an alternative issue in both fields of psychology and education. Studies that have been conducted in this area illustrate the role of EQ and its components in different aspects of one's life such as academic achievement, occupation, and social relationships. ...
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Emotional Intelligence (EQ) is considered as an alternative issue in both fields of psychology and education. Studies that have been conducted in this area illustrate the role of EQ and its components in different aspects of one's life such as academic achievement, occupation, and social relationships. Turning to a view to academic performance measurement, mathematics is considered as a science which can promote the learners' ability in order to respond to the ups and downs of every individual’s life. Most of the previous papers have investigated the relationship between EQ and mathematical Performance. The main feature of those studies were focusing on statistical analysis. To deal with this issue, this study proposes an alternative procedure not only is interested in employing non parametric models, such as Data Envelopment Analysis (DEA), but also provides the statistical analysis to assess the questioned relation. The proposed procedure can serve as an evaluation tool for educational policy and students ‘promotion. To do so, eighty-one individuals have been selected among Islamic Azad University (Yadegar-e-Imam Khomeini (RAH) branch) engineering students with simple random during the first midterm of academic year 2019-2020. Distributing a standard EQ questionnaire of Bradberry and Greaves [18] reveals EQ and its four components’ scores. The average of three completed math scores have presented mathematical performance quantity. The results of DEA point out no specific pattern between EQ and mathematical performance. The study also reveals that statistical analysis show a similar trend as efficiency analysis method did.
Esmat Baktash; Behjat Amoushahi; Mohammad Mehdi Behdad
Volume 1, Issue 2 , June 2014, , Pages 59-73
Abstract
DEA (Data Envelopment Analysis) is a linear programming method whose main purpose is comparing and evaluating a number of similar decision making units with different amounts of input and output. Using this method, one can rank efficient and inefficient companies and then among the efficient companies, ...
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DEA (Data Envelopment Analysis) is a linear programming method whose main purpose is comparing and evaluating a number of similar decision making units with different amounts of input and output. Using this method, one can rank efficient and inefficient companies and then among the efficient companies, identify the efficiency frontier. In ranking stock companies, one of the factors which have been overlooked in previous research is “Intellectual Capital” index. In this paper, based on this index, along with financial indices, the petrochemical companies listed on the stock exchange have been ranked by means of Data Envelopment Analysis method and then efficient and inefficient companies have been identified. Subsequently, employing Benchmark Approach, efficient units have been ranked. Also, to determine the importance of inputs, by applying Sensitivity Analysis, the model has been solved three times, each time removing one of the inputs and the difference between the obtained values and the values gotten from the primal model has been calculated. The results of the study show that among the 16 companies under study, 9 units have been known to be efficient and the “Intellectual Capital” index, as an input in DEA model, has a significant role in evaluating these units.
M. Bashirzadeh; S. Daneshvar; N. Azarmir
Volume 1, Issue 1 , March 2014, , Pages 1-11
Abstract
One of the applications of Data Envelopment Analysis (DEA) is in ranking of Decision Making Units (DMUs). When some DMUs are the same in efficiency score, this ranking results in failure. Various methods are introduced to rank efficient and inefficient DMUs and attempt to give a fully ranking in order ...
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One of the applications of Data Envelopment Analysis (DEA) is in ranking of Decision Making Units (DMUs). When some DMUs are the same in efficiency score, this ranking results in failure. Various methods are introduced to rank efficient and inefficient DMUs and attempt to give a fully ranking in order to improve the evaluation. Many articles are published in this field so that have some problems. In this paper, by considering undesirable outputs and extending the inefficient space, a complete ranking of DMUs is presented. On the other hands using facet as a complement of previous methods leads to a fully ranking.
Sahar Khoshfetrat; Farhad Hosseinzadeh Lotfi
Volume 1, Issue 1 , March 2014, , Pages 12-18
Abstract
As ranking is one of the most important issues in data envelopment analysis (DEA), many researchers have comprehensive studies on the subject and presented different approaches. In some papers, DEA and Analytic hierarchy process (AHP) are integrated to rank the alternatives. AHP utilizes pairwise comparisons ...
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As ranking is one of the most important issues in data envelopment analysis (DEA), many researchers have comprehensive studies on the subject and presented different approaches. In some papers, DEA and Analytic hierarchy process (AHP) are integrated to rank the alternatives. AHP utilizes pairwise comparisons between criteria and units, assessed subjectively by the decision maker, to rank the units. In this paper, a nonlinear programming (NLP) model is introduced to derive the true weights for pairwise comparison matrices in AHP. Genetic algorithm (GA) is used in order to solve this model. We use MATLAB software to solve proposed model for ranking the alternatives in AHP. A numerical example is applied to illustrate the proposed model.
