The goal of this study is to contribute to commercialization of the second-generation cellulosic biofuels (SGCBs) by reducing its operational cost. A hybrid simulation-based optimization approach is devised to design a cost-effective SGCB supply chain model. The approach includes feedstock yield estimation and location-allocation of feedstock storages between farms and refineries. An agent-based simulation (ABS) implemented in AnyLogic is utilized to estimate operational cost of a SGCB supply chain. The simulation-based optimization with adaptive replication (AR) is devised to find an appropriate SGCB network design in terms of operational cost. The approach is applied to a SGCB transportation network design problem in Southern Great Plains of U.S.
The output data from running the supply chain simulation model was applied to the transportation network design problem in Southern Great Plains of U.S. involving Alabama, Arkansas, Louisiana, Mississippi, Oklahoma, Texas, and Tennessee.