List of Articles

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  1 - Interval PROMETHEE II, TOPSIS and EDAS Approaches for Multi-Criteria Ranking Problem of the Bank Branches in Iran
  Saeid Torkan Ali Mahmoodirad Sadegh Niroomand Saeid Ghane
  Undoubtedly, rating bank branches is one of the essential tool managers use to promote branches. In this study, a multi-criteria problem applied in banking has been addressed. In this research, a framework for ranking 20 branches of Tose’e Ta'avon bank in Iran (Khuzesta More

  Undoubtedly, rating bank branches is one of the essential tool managers use to promote branches. In this study, a multi-criteria problem applied in banking has been addressed. In this research, a framework for ranking 20 branches of Tose’e Ta'avon bank in Iran (Khuzestan province) using decision-making methods has been considered as a case study. Essential criteria are selected through experts and research literature. Then, according to the uncertainty in some indicators and the elimination of defects related to the investigation at a certain point, the data is determined in the form of interval values. The weighting of the criteria using experts' opinions, interval Shannon entropy, and the linear combination of the two, and considering the final matrix extracted from three 4-month intervals (geometric mean of 3 matrices) using three approaches, namely PROMETHEE II, EDAS, and TOPSIS with interval values, the ranking of bank branches has been used for a case study. Then, benchmark tests are used to validate the methods to provide a fairer ranking. Finally, the managers can see the actual position of the branches in identify throughout the year and use it to improve the bank's performance. Manuscript profile
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  2 - Ridge Regression With Intuitionistic Fuzzy Input and Output‎: ‎A Parametric Approach
  Zahra Behdani Majid Darehmiraki
  Ridge regression is a model that is frequently used and has numerous effective applications‎, ‎particularly in the management of correlated factors in a multiple regression model‎. ‎Additionally‎, ‎multicollinearity poses a significant risk in fuzzy regression models wh More

  Ridge regression is a model that is frequently used and has numerous effective applications‎, ‎particularly in the management of correlated factors in a multiple regression model‎. ‎Additionally‎, ‎multicollinearity poses a significant risk in fuzzy regression models when it comes to predictions‎. ‎In order to solve this problem‎, ‎we bring together the fuzzy regression model with the ridge regression technique‎. ‎Regarding the evaluation of the coefficients of the ridge fuzzy regression model‎, ‎the algorithm that we have suggested makes use of the parametric estimation approach‎. ‎In this article‎, ‎we examine the ridge regression in the intuitionistic fuzzy environment‎. ‎We assume that the input and output data are intuitionistic fuzzy numbers‎. ‎Since in the regression analysis we need to calculate the distance between the variables‎, ‎we define a new fuzzy parametric distance‎. ‎Also‎, ‎the goodness of fit of the model with the indicators of the mean square of the prediction error has been investigated in simulation examples and real data‎. Manuscript profile
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  3 - A Compromise Solution Approach for Fuzzy Data Envelopment Analysis: A Case of the Efficiency Prediction
  Nam Hyok Kim Feng He Kwang-Chol Ri Son-Il Kwak
  The data envelopment analysis (DEA) a data-oriented approach for evaluating the relative performance of decision-making units (DMUs). The traditional DEA applies only to crisp data, whereas the data collected in the real world may be ambiguous and imprecise. The fuzzy D More

  The data envelopment analysis (DEA) a data-oriented approach for evaluating the relative performance of decision-making units (DMUs). The traditional DEA applies only to crisp data, whereas the data collected in the real world may be ambiguous and imprecise. The fuzzy DEA is an extension of the DEA using the fuzzy variable to deal with uncertain or imprecise data. This paper proposes two new fuzzy arithmetic-based DEA models with dynamic weights and common weights, formulated as multiple objective decision-making (MODM), and proposed models are represented as the linear programs providing the compromise solutions. The numerical experiment is illustrated to examine the validity of the proposed models, and the experiment shows that the proposed models give better results than other models. The proposed fuzzy DEA models are applied to predict the energy efficiency of 40 iron and steel enterprises in China. Manuscript profile