Designing a resilient and reliable biomass-to-biofuel supply chain under risk pooling and congestion effects and fleet management

Abstract The utilization of renewable biomass as feedstock for biofuel production has been gaining prestige to mitigate carbon emissions. This paper aims to render an optimization model for designing a resilient and reliable biomass-to-biofuel supply chain network in which multi-modal terminals, biorefineries, and their connection link could be faced with disruption. For this purpose, risk-averse optimization, transitional probabilities, and spatial statistics models are employed. What is more, to overcome the repercussions of uncertain demand and the availability of raw materials, risk pooling and M/M/1 queuing system are considered. Finally, since the proposed model is an NP-hard problem, two meta-heuristic algorithms called improved ray optimization and colliding bodies optimization are employed to solve the proposed model. Computational results reveal that by increasing 20% of the conversion rate of biomass to biofuel, which leads to increase biomass supply, biofuel production increases by 20.88%, and the SC cost declines by 9.32% due to the better capacity distribution of bio-refineries. Also, the proposed model increases by 20.87% in the total SC costs under random disruptions than the risk-neutral model, although the failure costs of SC decline by 80.45%.