Stochastic optimization of cellulosic biofuel supply chain incorporating feedstock yield uncertainty

The global goal to reduce dependence on fossil fuels and to mitigate greenhouse gas emissions has resulted in research focused on environment friendly and socio-economically sustainable renewable energy sources. However, commercial production of bioenergy is constrained by biomass supply uncertainty and associated costs. This study presents an integrated approach to determining the optimal biofuel supply chain considering biomass yield uncertainty. A two-stage stochastic mixed integer linear programming is utilized to minimize the expected system cost while incorporating yield uncertainty in the strategic level decisions related to biomass production and biorefinery investment. Applicability of the stochastic model is illustrated through a case study of switchgrass-based biofuel in west Tennessee. (C) 2019 The Authors. Published by Elsevier Ltd.