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      • Open Access Article

        1 - Evaluation of Countries Environmental Efficiency Using Data Envelopment Analysis
        مینا مشفق محسن رستمی مال خلیفه
        Over the last few decades, there has been a dramatic increase in public attention to environmental issues. As a consequence of the growing concerns about environmental quality, climate change, and pollutant emission, which are key elements of sustainable development, on More
        Over the last few decades, there has been a dramatic increase in public attention to environmental issues. As a consequence of the growing concerns about environmental quality, climate change, and pollutant emission, which are key elements of sustainable development, one of the main challenges is measuring environmental efficiency. The main purpose of this study is to evaluate the ecological efficiency of countries and rank countries based on data envelopment analysis (DEA) method, considering the favorable and unfavorable outputs (7 inputs and 7 outputs) affecting climate change in 2020 in 176 countries. The units were evaluated by CCR model and Also AP model in order to ranking both efficient units and inefficient units. The results show that the environmental efficiency of the selected countries is 80.60% on average, of which Iran ranks 140th with an efficiency of 0.58 and Iceland, Singapore and Lesotho have the highest environmental efficiency, respectively, as well as Sierra Leon, the Philippines, and Pakistan have the lowest environmental performance, respectively. Manuscript profile
      • Open Access Article

        2 - A new robust optimization approach to most efficient formulation in DEA
        Reza Akhlaghi Mohsen Rostamy-Malkhalifeh Alireza Amirteimoori Sohrab Kordrostami
        In this article, we investigate a new continuous linear model with constraints for the direct selection of the most efficient unit in the analysis of data coverage presented by Akhlaghi et al. (2021) on uncertainty robust optimization. Considering the importance of inco More
        In this article, we investigate a new continuous linear model with constraints for the direct selection of the most efficient unit in the analysis of data coverage presented by Akhlaghi et al. (2021) on uncertainty robust optimization. Considering the importance of incorporating uncertainty into performance evaluation models in the real world and its increasing application in various problems, we propose a robust optimization approach. Given the discrete and non-convex nature of the introduced models for selecting the most efficient decision-making unit, examining the dual and finding an optimistic scenario is practically impossible. Therefore, by utilizing the linear model presented by Akhlaghi et al. (2021) with constraints for identifying the most efficient unit, we can investigate the robustness of the desired model using(BS )Bertsimas and Sim's (2004) robust estimation method while also considering uncertainty. We aim to demonstrate that employing a robust formulation leads to reliable performance in uncertain conditions Manuscript profile