According to significant challenges of the banks, there is a greater need to assess the existing banking system and implement corrective actions. In this paper, the financial soundness of 11 Iranian private banks is evaluated by using the CAMELS indicators (Capital adequacy, Asset quality, Management, Earning, Liquidity, and Sensitivity to market risk). The weights of indicators are determined using the Best-Worst Method (BWM). Data Envelopment Analysis (DEA) is consequently used to calculate the efficiency score of the Decision-Making Units (DMUs). Principal Component Analysis (PCA) is used to validate the DEA results. Also, several sensitivity analyses are conducted on private banks. The intuitive results of sensitivity analysis prove accurate as demonstrated by statistical tests. The results of sensitivity analysis and statistical tests demonstrate that Iranian private banks have the best performance in terms of the indicators of Management and Capital adequacy, and the poorest performance in terms of Asset quality. Also, using the Strengths-Weaknesses-Opportunities-Threats (SWOT) matrix, the authors present appropriate strategies for improving the performance of the banking system. To the best of our knowledge, the present study for the first time aims to assess and improve financial soundness of private banks by using a combination of qualitative and quantitative methods.

As one of the most complicated and challenging networks among healthcare systems, the organ transplant network necessitates an effective supply chain network design. In this article, a bi-objective mixed integer nonlinear programming (MINLP) location-allocation model is proposed to design the organ transplant supply chain network, with the objectives of minimizing overall costs (including strategical and operational costs) and the number of unsatisfied demands under uncertainty. The developed model calculates the optimum number of facilities to be established and equipped for each organ, the flows between them, and the optimal allocation of cold chain vehicles, which is a combination of similar works in this context with cold chain and resource allocation as one of the novelties of this paper. Moreover, the preciousness of human life necessitates a policy for allocating organs. Hence, in this study, high-risk recipients, who are more likely to die in case of unmet demand, are prioritized above low-risk ones to prevent mortality as much as possible. This article also takes transportation constraints into account in the effort to minimize carbon emissions, one of the most challenging environmental concerns of the present day. Numerical experiments demonstrate the applicability of the developed model, and a case study is presented to compute the optimal solutions of the proposed methodology. Finally, various sensitivity analyses are performed to provide managerial insights.

During the past years, many kinds of research have been done in order to reduce the cost of transportation by using different models of the vehicle routing problem. The increase in the amount of pollution caused by vehicles and environmental concerns about the emission of greenhouse gases has led to the use of green vehicles such as electric vehicles in the urban transport fleet. The main challenge in using electric vehicles with limited battery capacity is their long recharging time. For this purpose, several recharging stations are considered in the transportation network so that if the battery needs to be recharged, the electric vehicle can recharge and complete its journey. On the other hand, due to the limited amount of the electric vehicle's energy, the fuel consumption of this fleet is highly dependent on their load, and it is necessary to consider their load in the planning. In this article, the problem of routing electric taxis is presented considering the economic and environmental aspects of implementing electric taxis for city services. Despite other studies that have only focused on reducing energy consumption or minimizing distance traveled by electric vehicles, for the first time, the problem of urban electric taxi routing has been modeled by considering different types of electric taxis with the aim of achieving the maximum profit of this business. The use of a heterogeneous fleet in this study leads to wider coverage of different types of demand. Therefore, a mathematical programming model is presented to formulate the problem. Then, several problem examples are designed and solved for validation purposes, and the simulated annealing algorithm (SA) will be introduced and used to solve large-scale problems.