Integrating GIS with optimization method for a biofuel feedstock supply chain

Taking forest biomass, defined here as roundwood pulpwood, as feedstock, this study focused on locating bioethanol facilities and designing the bioethanol feedstock supply chain to minimize the total system cost. For this purpose an integrated approach combining Geographic Information System based analysis with optimization modeling method was developed. Nine candidate bioethanol facilities were preselected based on the GIS method and served as input for the optimization modeling followed. The total system cost and the delivered feedstock cost were calculated under demand and supply uncertainties. Both cost values increase significantly as the annual bioethanol demand grows or the biomass availability decreases. This is because more feedstocks are required to be hauled from longer distances to support a larger scale bioethanol facility or several smaller ones. It is also found that Gaylord shows up as one of the optimized candidate no matter what the demand or supply is. The optimization model and identified locations provides decision makers an integrated decision support system to determine optimized cost, energy use, and GHG emissions for candidate locations. (C) 2017 Elsevier Ltd. All rights reserved.