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

H. Gilani, H. Sahebi, Fabricio Oliveira*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

31 Citations (Scopus)
117 Downloads (Pure)


Issues that highly threaten the global economy today are the high fossil-fuel price fluctuations, considerable air pollution, and the truth that these sources are not unlimited and will eventually finish someday. Hence, researchers have been attracted by the biomass, especially sugarcane, as a source of renewable energy to produce bioethanol and biofuel. This research is aimed to formulate a three-phase robust supply chain network design optimization model to produce bioethanol from sugarcane using the fuzzy integrated data envelopment analysis method to select suitable cultivation lands as potential points. Since the objectives are to maximize the profit, minimize environmental effects, and maximize the social performance, and some parameters are naturally uncertain, use has been made of a robust possibilistic programming model to deal with them considering the possibility of transportation disruptions. The model performance has been illustrated through a case study in Iran and it has been validated using the realization method.

Original languageEnglish
Article number115653
Number of pages19
JournalApplied Energy
Publication statusPublished - 15 Nov 2020
MoE publication typeA1 Journal article-refereed


  • Data envelopment analysis
  • Disruption
  • Robust possibilistic programming
  • Sugarcane-to-bioethanol supply chain network
  • Sustainable supply chain


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