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Multi-period stochastic optimization of a sustainable multi-feedstock second generation bioethanol supply chain − A logistic case study in Midwestern United States

Osmani, Atif, Zhang, Jun
Land use policy 2017 v.61 pp. 420-450
Panicum virgatum, bioethanol, biorefining, case studies, land use, mathematical models, planning, supply chain, uncertainty, Midwestern United States
This work proposes a multi-objective optimization model to design a sustainable multi-period second generation biomass-to-bioethanol supply chain under multiple uncertainties. The objective is to simultaneously maximize the economic, environmental, and social performance. The strategic decisions such as land allocation for switchgrass cultivation, biorefinery locations and capacities, and the biomass-to-bioethanol conversion pathway are determined for each planning period which are staggered across the entire planning horizon. The augmented ε–constraint method is used to trade-off among the competing objectives and to obtain feasible solutions that achieve desired levels of sustainability. In order to solve the proposed stochastic optimization model efficiently and effectively, this work proposes a solution approach involving sequential application of a modified Sample Average Approximation method and Benders decomposition. A case study is presented to demonstrate the effectiveness of the proposed mathematical model and its impact on land usage and sustainability.