نشریه پژوهش های نوین در تصمیم گیری
سال ششم شماره 4 (زمستان 1400)

Today, the need to use efficiency measurement systems in the modern banking industry has become increasingly apparent. Therefore, the efficiency of banks needs to be forecasted so that future economic growth can be monitored in future decisions. This paper designs a new integrated model based on the Stochastic Data Envelopment Analysis (SDEA) model and the Principal Component Analysis (PCA) method in a dynamic environment to forecast the efficiency of branches in the modern banking industry by considering variable returns to scale for them. In order to deal with the uncertainty in efficiency forecasting, the inputs and outputs of the branches are designed as triangular fuzzy stochastic variables with normal distribution. In this study, Monte Carlo (MC) simulation and meta-heuristic algorithms have been used to solve the proposed model. Finally, in order to evaluate the performance and accuracy of the proposed integrated model, a case study based on modern banking indicators has been presented to forecast the efficiency of the future financial period of the branches and the results have been analyzed.

Today, social media has become a place for users to comment on various topics, including consumer products, and these comments have become a valuable resource for sentiments analyzing and extracting customer expectations of products. This subject provides companies with a good opportunity to redesign their products based on user feedback. In this study, to provide recommendations to the design units of detergent products, we used sentiment analysis of customers and consumers of this products on social media. More than 4200 tweets were extracted from Twitter in 2019 based on the research topic and refined and tagged during the pre-processing of the texts. Afterwards, we analyzed the emotions using fuzzy logic and topic modeling. We have used topic modeling to find the features mentioned in the comments for a better approach in the design units, and fuzzy logic to obtain the degree of polarity of ideas into 5 categories: very positive, positive, neutral, negative and very negative. We used confusion matrix for evaluating research model and an accuracy of 86.15 % has been recorded.In this research Python libraries are used for data gathering, cleansing and analysis.

The management of production and distribution of electricity is one of the most important issues in developing countries and it is the framework for development. Because of limitations and different technologies and existence of so many factors on electricity management, consideration such problem as a single level approach is not reasonable. So, in this paper a bi-level follower leader approach is considered in which the follower is the company of Iran management network electricity and the leaders are some operation companies. Based on the accomplished researches, this paper is the first bi level attempt in the field of production and transmission management of electricity and it is localized with the special specifications in Iran. The objective function is minimizing the emission cost of greenhouse effect and distribution costs and consumed fuels and startup for follower and leader respectively. Because of high complexity of presented model, a Simulated Annealing is used for solving the problem. The results of current study could be used for improvement of Iran management network.

In this paper, the minimization problem of a geometric objective function with a single-term exponent subject to bipolar fuzzy relation equations is studied with the max-product composition operator. This paper intends to update the lower bound of its objective function by simplifying the problem and design an algorithm to find the initial upper bound for the optimal objective value of the problem based on its initial (or updated) lower bound. We then develop a modified branch-and-bound method based on the bound to solve the above problem. We also design an efficient algorithm to solve the problem according to the above algorithm and the developed branch-and-bound method. According to the proposed upper and lower bound, the developed branch-and-bound method examines a much less number of nodes to find the optimal solution. Hence, the rate of computations is significantly reduced. Finally, a numerical example is provided to illustrate the algorithm and its performance.

The reform of the structure in the health system has made many changes with the aim of improving this system. One of them is the health system transformation plan, which has led to the introduction of new mechanisms, which have complicated communication, challenges and, finally, serious conflicts between insurance organizations and hospitals.In this study, in order to improve the inter-organizational problems, the conflicts and contradictions between the stakeholders of this issue have been studied and structured.In this paper, participants were first identified using the journey making. Then, by drawing a power-interest diagram, the role of each participant was determined, and the main actors were identified. Next, the problem of hospital waste management actors was structured by drama theory. Therefore, the priorities and decision options of each of the actors at a negotiating table were analyzed and the problems of non-cooperation and conflict between them were evaluated. Finally, strategies to solve problems in the management of hospital wastes were presented.The results show that the most conflict between waste organizations and hospitals is formed and the most important type of problem between organizations is the problem of rejecting each other's options.Conflicts caused by rejection dilemma can be considered as the best type of conflict that can be turned into cooperation by negotiating options and a little flexibility, compromise and, of course, innovation in offering newer options.

In an organization, employees are often evaluated (ranked) by multiple supervisors (or co-workers) in different time periods. Providing a single ranking based on these evaluations in such a way that it has the most compatibility and consistency with the provided evaluations is called rank aggregation. This rank aggregation problem, which has wide applications in various sciences, has been studied extensively theoretically in mathematics and computer science. In this paper, we study for the first time, the application of rank aggregation in the field of performance appraisal. In this application, the performance rankings of employees are given by a number of evaluators and the goal is to provide a final ranking for the employees that has the most similarity to the given evaluations. Other than obtaining the most consistent rankings, we show that more inference results like the quality of the evaluators and informal relationships between individuals can be obtained as by-product of this process of rank aggregation.

Investigating dynamic relationships among effective variables for sustainable industrial development can help to understand the industrial ecosystem's behavioral responses to development policies. The purpose of this study is to develop a system dynamics model for sustainable development and development policy evaluation model in Aras free zone. In this paper, system dynamics modeling framework has been used to understand the interactions among social, economic, and environmental components. In the next step, the robustness of the model is examined using time series data between 2008 and 2018. Thereafter, sensitivity analysis has been conducted to evaluate the influence of the possible changes in the key drivers through simulation technique on policy efficiency in Aras economic region. The simulation results show that the development in the manufacturing industry based on the advice from the "Development in Aras economic zone" Scheme has led to the situation where the carrying capacity has been failed, hence the sustainability goals are unattainable. the results show that the service section has the least destructionto the environment. Developing industrial development strategies by considering its environmental and social dimensions and directing investments to the service sector can be considered as solutions to achieve the goals of sustainable development of the Aras Free Zone.

Four - level supply chain is a chain of different products because of continuous and significant changes in the quality of food products throughout the supply chain. The aim of this paper is designing a fuzzy multi - objective model for optimization of facility location in a perishable products of supply chain using the combination of two heuristic Banders and Lagrange algorithms. The present study is applicable in terms of purpose and data collection method. in this study, the mathematical model for the problem of locating facility in a four - level supply chain for perishable products is presented at the same time the supply chain costs, order delivery time, emissions and customer satisfaction level. to evaluate the validity of the research, the mathematical model was studied in Kaleh food industries and the research problem was presented in the form of a nonlinear model of complex integer programming. the results of the proposed algorithm in the case study of the solution and the results of the algorithm performance based on standard indices and finally computational results show the performance of the algorithm for a wide range of different.

Data envelopment analysis (DEA ) is a technique to evaluate the relative performance of a set of decision - making units ( DMUs ) . Corresponding to each inefficient DMU , an efficient benchmark on efficient frontier is determined and inefficient DMUs are projected to this benchmark by increasing their outputs and decreasing inputs . In this paper , a DEA - based procedure is proposed to determine an ideal benchmark to each inefficient unit . Our proposed benchmark dominates the unit under evaluation and it is a convex combination of projection points obtained from different aspects : cost, revenue efficiencies and the closest distance . A n important point is that although the obtained benchmark is not necessarily an efficient point, however , it dominates the unit under consideration . At the end of the paper , the proposed model would be implemented on a simple numerical example .

Fuzzy expert systems are intelligent systems which can be used to obtain better results in evaluating the performance of the banking system. The purpose of this study is to evaluate the performance of bank branches using fuzzy variables beside financial variables. In this study, firstly, the rules of the data were extracted by implementing data mining algorithms on the financial data of branches. In the next step, by obtained rules of financial data and along with fuzzy variables, a fuzzy expert system is designed in order to achieve a system that can comprehensively evaluate the bank branches performance. For designing the considered expert system, nine fuzzy variables such as branch location, customer loyalty, employee satisfaction, customer satisfaction, creativity and innovation, branch appearance, staff appearance, employee stability and also the output of financial rates have been used. Decision tree and C.5 algorithms have been used in order to extract the rules in the branch data. MATLAB fuzzy inference system has been used to design the fuzzy expert system also. The results of the research illustrated the hidden knowledge of the branch data can be extracted via data mining and the performance of bank branches can be evaluated as a comprehensive information system by fuzzy expert systems.

Data envelopment analysis(DEA) has been extended to cross-efficiency evaluation to better discrimination and ranking of decision making units(DMUs). Unfortunately, the optimal weights generated may not be unique which has reduced the usefulness of this powerful method. In addition, due to alternative optimal solutions, zero weights can be seen in cross-efficiency evaluation. To solve these problems, first the concept of perturbation and generation of unique solution is introduced. Then an alternative evaluation approach contains a perturbed model, is proposed based on the performance analysis without slacks. This modified model can generate unique and non-zero optimal weights, simulteneously. Furthermore, the structure of the model can ensure the dissimilarity of the generated optimal weights. All these factors make the cross-efficiency evaluation results more satisfied and acceptable by all the DMUs. Finally, the proposed approach is applied on a real case study of of Iranian Gas Company and the results show that in contrast to standard DEA model the propsed model can perform well.