Bioethanol supply chain system planning under supply and demand uncertainties

A mixed integer stochastic programming model is established to support strategic planning of bioenergy supply chain systems and optimal feedstock resource allocation in an uncertain decision environment. The two-stage stochastic programming model, together with a Lagrange relaxation based decomposition solution algorithm, was implemented in a real-world case study in California to explore the potential of waste-based bioethanol production. The model results show that biowaste-based ethanol can be a viable part of sustainable energy solution for the future.

► We optimize bioenergy supply chains from wastes to ethanol. ► Two-stage stochastic programming is used to incorporate supply and demand uncertainties. ► The large-scale problem is solved via Lagrange relaxation based decomposition method. ► Results suggest that waste-based cellulosic ethanol can be a part of sustainable energy solution.