Simulation-based approach for the optimization of a biofuel supply chain

The billion-ton study lead by the Oak Ridge National Laboratory indicates that the U.S. can sustainably produce over a billion ton of biomass, annually. However, the delivery of the biomass required to meet the required goals is particularly challenging. This is mainly because of the physical properties of biomass. This paper focuses on the use of agricultural residues to produce second-generation biofuels. Second generation biomass exhibits more quality variability (e.g., higher ash and moisture contents) than first generation. The purpose of this study is to quantify the cost of imperfect feedstock quality in a biomass-to-biorefinery supply chain (SC) and to develop a discrete event simulation coupled with an optimization algorithm for designing a biofuel SC. This paper presents a novel optimization approach based on an extended Integrated Biomass Supply and Logistics (IBSAL) simulation model for estimating the collection, storage, and transportation costs. The presented extension of the IBSAL considers the cost incurred for having imperfect feedstock quality and finds the optimal SC design. The applicability of this methodology is illustrated by using a case study in Ontario, Canada. A converging set of non-dominated solutions is obtained from computational experiments. Sensitivity analysis is performed to evaluate the impact of different scenarios on overall costs. Preliminary results are presented.