(128c) GIS-Based Two-Stage Stochastic Facility Location Problem Considering Planting Plan Uncertainty

Due to growing demands for bioenergy and bioproducts, research interests and efforts have been stimulated in the past decades to achieve a cost-efficient and sustainable biomass supply chain. Guayule (parthenium argentatum), as a flowering shrub growing in arid or semi-arid regions, has attracted scholars' attention these days. It is a good alternative source of natural rubber other than rubber trees. Some classic and well-studied optimization models are applied to configure and manage a biomass supply chain, where facility location problem is of great concern in decision making along the supply chain. In this work, a two-stage stochastic mixed integer programming (MIP) is formulated to capture the uncertainty coming from planting plan of guayule. The optimal location for a processing plant, which converts guayule to different products is selected from several candidates pre-selected by utilizing a Geographic Information System (GIS). An illustrative case study related to guayule in two counties of Arizona is also provided in this work.