Bioethanol (bio-EtOH) is commonly used as a renewable biofuel additive for gasoline. A novel technology producing bio-EtOH from anaerobic digestion of organic waste (OW) has recently attracted attention. This work presents a deterministic mixed integer linear programming model for the optimal location of OW-based bio-EtOH biorefineries. The proposed model considers OW treatment location, bio-EtOH biorefineries, and truck transport links as a supply chain network (SCN) approach. The objective function of the developed model is to minimize the total bio-EtOH levelized cost (ELC) while satisfying the model constraints consisting of equalities (e.g., mass and energy balances for the bio-EtOH biorefinery) and inequalities (e.g., capacity of the bio-EtOH refinery, truck transport) to meet the regional demands of bio-EtOH. To validate the optimization model, a case study based on a real scenario for South Korea in 2030 was conducted for different bio-EtOH blending rates (E10, E20, E85, E100). The case study results indicate that ELC of E10 containing 10% bio-EtOH from OW products combined with gasoline is USD 3.65/gallon. As the blending rate of bio-EtOH increases, ELC increases to USD 4.36/gallon for E20, USD 8.99/gallon for E85, and USD 10.05/gallon for E100. The optimization results can help determine SCN strategies for an OW-based biofuel economy.