Optimally Locating Biorefineries: A GIS-Based Mixed Integer Linear Programming Approach

Biofuels have recently attracted enormous attention from researcher in various disciplines. Most existing studies are focused on the biofuel production process to reduce production cost and improve efficiency. Although the cost of transporting bulky and unrefined biomass feedstock is also very significant compared to the total cost for producing biofuels, much less attention has been given to research on reducing the biomass transportation cost. This study is aimed to develop a GIS-based decision support tool for finding the best biorefinery locations to minimize the biomass transportation cost. The developed GIS tool first obtains reliable biomass distribution data from remote sensing images. Based on the biomass distribution data and other information such as transportation network, a mixed integer linear programming model is developed and integrated into the GIS tool to find the optimal locations of biorefineries. The developed GIS tool is applied to a case study in South Carolina using switchgrass as the biomass feedstock. The GIS-based framework established in the study not only provides a practical tool to inform decision-making but also serves as a versatile prototype to guide future research endeavors in biorefinery location selection and biomass transportation cost analysis