RESUMO
The aim of this study was to develop a scenario optimization model to address weather uncertainty in the Biomass Supply Chain (BSC). The modeling objective was to minimize the cost of biomass supply to biorefineries over a one-year planning period using monthly time intervals under different weather scenarios. The model is capable of making strategic, tactical and operational decisions related to BSC system. The performance of the model was demonstrated through a case study developed for Abengoa biorefinery in Kansas. Sensitivity analysis was done to demonstrate the effect of input uncertainty in yield, land rent and storage dry matter loss on the model outputs. The model results show that available harvest work hours influence major cost-related decisions in the BSC.