Concerning global warming and the Greenhouse gas (GHG) effect, clean energy resources have captured researchers' interest recently. Biomass materials are among important biofuels and bioenergy production resources that have the potential to replace fossil fuels. Using b
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Concerning global warming and the Greenhouse gas (GHG) effect, clean energy resources have captured researchers' interest recently. Biomass materials are among important biofuels and bioenergy production resources that have the potential to replace fossil fuels. Using biomass materials leads to a decline in GHG emission and air pollution levels, not being dependent on fossil fuels, and provide energy security. Due to the importance of bioenergy and biofuels, a multi-product, multi-period, and green mathematical model has been developed to improve economic and environmental objectives for bioethanol and the electricity supply chain. It includes the following decisions: determining production centers' location and capacity, technology selection, determining inventory holding level, biomass type selection, allocation, amount of material flow, and determining transportation modes. In this study, a scenario-based robust compromise programming approach (SRCP) is developed for the bi-objective solution of the provided mathematical model and determining Pareto optimal points under uncertain conditions. Finally, the performance and effectiveness of SRCP are provided, and the results obtained from the case study in Iran are analyzed. According to the results, Annual electricity and bioethanol production capacity are at least 8000 million kWh and 1250 kton, respectively, satisfying 10% of electricity and 5% of gasoline demand in 6 provinces of Iran. The sensitivity analysis also shows that equal weight for both objectives can be more logical for decision makers.
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