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Prioritization of biodiesel development policies under hybrid uncertainties: A possibilistic stochastic multi-attribute decision-making approach

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  • Rezaei, Mohsen

Abstract

Decision-making in the field of energy policy is very difficult due to the existence of various uncertainties in this area. Classical multi-criteria decision-making (MCDM) methods are effective only in stable conditions and ignore future uncertainties. Therefore, in this study, a novel concept called possibilistic stochastic multi-attribute decision-making (PSMADM) is presented. In this approach, the decision matrix is varied in each scenario. Since the values of weights and scores in each scenario are imprecise, the possibilistic programming is used to confront this kind of uncertainty. The approach is used to rank Iran's biodiesel development policies. In addition, a new scenario planning method is presented in this research for designing biodiesel scenarios. Fuzzy SWARA and fuzzy EDAS methods are used to solve the different MCDM models. The results are validated by comparing with VIKOR model and evaluating by Spearman's rank correlation test. The Spearman's rank values for the scenarios are 0.9394, 0.8909, and 0.9636, which show a strong positive correlation between the results. Lastly, an approach is suggested for aggregating the results of scenarios to final ranking the alternatives. The results indicate that the best alternative for the development of biodiesel is “supporting the private sector for more participation in this field”.

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  • Rezaei, Mohsen, 2022. "Prioritization of biodiesel development policies under hybrid uncertainties: A possibilistic stochastic multi-attribute decision-making approach," Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:energy:v:260:y:2022:i:c:s0360544222019697
    DOI: 10.1016/j.energy.2022.125074
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