Data Envelopment Analyses
Gholamreza Panahandeh Khojin; Abbas Toloie Ashlaghi; Mohamad Ali Afshar Kazmi
Abstract
The purpose of this study is to combine two methods of data envelopment analysis and neural network in order to provide an optimal model for ranking inefficiency factors in the Iranian banking industry. First, through the study of theoretical foundations and interviews with banking experts, efficiency ...
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The purpose of this study is to combine two methods of data envelopment analysis and neural network in order to provide an optimal model for ranking inefficiency factors in the Iranian banking industry. First, through the study of theoretical foundations and interviews with banking experts, efficiency evaluation indicators in the banking industry were identified and finalized. In order to evaluate the efficiency of the units in the statistical population of the study, data envelopment analysis technique was used, especially the modified goal programming data envelopment analysis model, which was identified from 32 managements, 3 efficient managements and 29 inefficient managements. Then, the branches of inefficient management were evaluated and using the information of inefficient branches, the neural network matrix was prepared to identify the causes of inefficiency and the results were analyzed with different neural network models. The model with the lowest mean square error will be selected as the optimal model to determine the inefficiency factors. As a result, the self-organized mapping model with hyperbolic tangent transfer function and 0.9 momentum training rule was selected. By analyzing the sensitivity of this method, the indicators of provincial liquidity share, personnel distribution and operating costs were selected as the most important factors of inefficiency.
meta-heuristic algorithms
Ebrahim Farbod; Alireza Hamidieh
Abstract
Purpose: The purpose of this study is to explain the impact of green supply chain on economic performance, emphasizing the mediating role of green innovation, environmental management and quality management in companies listed on the Tehran Stock Exchange.Methodology: In this research, the multivariate ...
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Purpose: The purpose of this study is to explain the impact of green supply chain on economic performance, emphasizing the mediating role of green innovation, environmental management and quality management in companies listed on the Tehran Stock Exchange.Methodology: In this research, the multivariate perceptron neural network approach and modeling of variance-based structural equations in SPSS26 and SmartPls3.3.3 software have been investigated.Findings: The results show that green supply chain management affects economic performance and increases green innovation, environmental management and quality management of economic performance. The establishment of a green supply chain has led to the observance of environmental requirements, and by observing environmental requirements, labor productivity is improved through specialized training of employees.Originality/Value: In previous studies have not considered the pros and cons of the relationship between environmental management and labor productivity. In this study, according to the selection of companies listed on the Tehran Stock Exchange during the covid-19 period and the statistical sample selected by systematic elimination method and available sampling, these views were examined. Also, in the research method, most researches have only fitted the model with structural equations and regression equations, while in this research, the proposed model fits with multilayer perceptron neural network method and variance-based structural equations and finally to evaluate the performance prediction comparison model. Economically, the root mean square error index is used
Combinatorial Optimization
Ahmad Yousefi Hanoomarvar; Maghsoud Amiri; Laya Olfat; Alireza Naser Aadrabadi
Abstract
Purpose: The proposed model is a time-cost-quality trade-off model with three objective functions: minimizing project completion time, minimizing total project cost, and maximizing total quality of activities in a PERT network with multi-mode activities.
Methodology: After presenting the appropriate ...
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Purpose: The proposed model is a time-cost-quality trade-off model with three objective functions: minimizing project completion time, minimizing total project cost, and maximizing total quality of activities in a PERT network with multi-mode activities.
Methodology: After presenting the appropriate mathematical model, based on the design of the experiments, the possible levels of each decision variable were determined. Then, using the simulation process, random values of decision variables and response variables were obtained each time, and by using neural networks, we established a neural network model. To solve this model, two algorithms NSGA-II and MOPSO were used.
Findings: To evaluate the efficiency of the model, the designed model was implemented in the maintenance department of Abtin Ardakan Steel Company. According to the results, it is found that the NSGA-II algorithm has better performance than the MOPSO algorithm.
Originality/Value: In this paper, a model was presented that by eliminating unrealistic assumptions and taking into account the realities of the project is closer to reality than the models presented in this field and has more application in practice.