چكيده به لاتين
Nowadays, oil price fluctuation, fossil fuels depletion, and the potential environmental impact of these energy resources are highly threaten the global economy. Developing the renewable resources, hence, is quite unavoidable. Sugarcane, as a source of renewable energy, can be converted to bioethanol. Therefore, this study has proposed a mixed integer linear programming to design an international network of sugarcane-to-biofuel supply chain. The data envelopment analysis method in employed in order to select suitable lands to cultivate sugarcane. The nominated lands is considered as the potential points in the network design model. To deal with uncertainty, robust optimization approach is employed in order to maximize the profit earned from the bioethanol sales at the foreign/domestic markets, minimize the environmental impacts caused by this supply chain activities, and maximize this network generated employment. The multi-echelon supply chain model involves different production/storage capacities, bio-refineries technologies, and transportation modes. The optimal production capacity/technology, the appropriate transportation mode in each route, and the bio-refineries’ development capacities have been specified by this supply chain configuration. The biofuel export price and the domestic/foreign markets’ demands are among the SC uncertain parameters addressed through the robust possibilistic programming. Finally, the tri-objective model has been solved using an approach that considers the decision maker’s preferences; the model performance has been verified by a case study performed in Iran. To verify the robust model’s efficiency the DLP realization model is, also, formulated.
