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

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