Sustainable sugarcane-to-bioethanol supply chain network design: A robust possibilistic programming model

Abstract

Issues such as high fossil-fuel price fluctuations, considerable air pollution, and the realization that fossil sources are not unlimited threaten the global economy. Hence, researchers have been attracted by biomass, especially sugarcane, as a source of renewable energy to produce bioethanol and other biofuels. This research proposes a three-phase robust supply chain network design optimization model to produce bioethanol from sugarcane. Fuzzy integrated data envelopment analysis method is employed to select suitable cultivation lands as supply potential points. The model considers sustainability in its implementation so that the objectives are to maximize the profit, minimize environmental effects, and maximize social performance. Since some parameters are naturally uncertain, a robust possibilistic programming model is proposed, considering the possibility of transportation disruptions. The model performance has been illustrated through a case study in Iran. Finally, the results of the mathematical model have shown that the recommended supply chain design is justifiable. Practical strategic insights include recommendations for locating refineries in seven provinces (Gilan, Kermanshah, Hamedan, Semnan, Khorasan Razavi, Khouzestan, Kihkooliye). These results have been validated using a simulation-based approach, which demonstrates that the proposed model recommends decisions that more suitable than the deterministic model in terms of average and standard deviation of objective values.