Designing a resilient and reliable biomass-to-biofuel supply chain under risk pooling and congestion effects and fleet management. (25th January 2021)

• Record Type: Journal Article
• Authors: Khezerlou, H. Soleimanian; Vahdani, Behnam; Yazdani, M.
• Is Part Of: Journal of cleaner production. Volume 281(2021)
• Publication Date: 2021-01-25
• Subjects: Biomass supply chain -- Disruption -- Risk measures -- Risk pooling -- Congestion -- Meta-heuristic; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2020.125101
• Languages: English
• ISSNs: 0959-6526

Abstract

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%. Graphical abstract: Image 1 Highlights: Presenting a resilient and reliable biomass-to-biofuel supply chain. Applying conditional-value-at-risk and absolute-semi deviation to reflect risk measure. Considering the disruptions of two types of facilities and connecting link among them. Considering risk-pooling and congestion to mitigate demand uncertainty and seasonality effect. The proposed framework declines the failure costs of the supply chain by 80.45%.