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As the global climate crisis worsens and fossil fuels deplete, renewable energy sources have become more appealing. Biofuel is one of the promising sources produced from multiple biomass sources, as long as it does not compromise food security. In this direction, a multiperiod mixed-integer linear programming model incorporating three types of biomass simultaneously is developed to provide a second- and third-generation biofuel supply chain. The proposed model minimizes the total annualized cost by selecting raw materials, locating production facilities, placing storage facilities, and identifying optimal material flows by defining a deference path for each feedstock. A case study addressing bioethanol production in South Korea was then conducted to evaluate the performance of the developed model; the results demonstrated a clear reduction in the total annualized cost by incorporating multiple feedstocks. Using multiple feedstocks allowed for the total ethanol demand of South Korea to be met using harvested biomass, thereby drastically reducing import costs. Refinery costs accounted for the large majority of the remaining costs. A sensitivity analysis was also conducted to assess the effect of uncertainty associated with some economic and production parameters.

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Owing to the increasing scarcity of fossil fuels and environmental concerns, renewable energy sources have gained significant attraction. In this study, we explore multi-objective function optimization to realize a strategic...

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