An optimization-based design methodology to manage the sustainable biomass-to-biodiesel supply chain under disruptions: A case study

Abstract

The detrimental effects of excessive fossil fuel consumption have recently become a major global concern. Moreover, fuel supply chains are vulnerable to disruptive and operational risks. This study proposes a robust-stochastic approach to design a resilient sustainable biodiesel supply chain from Jatropha and waste cooking oil, while facilities and transportation links are vulnerable to multiple site-dependent disruptions. The main contributions are implementing preventive resiliency strategies to manage risks, integrating sustainability and resiliency, and selecting biodiesel conversion technology based on byproducts’ demands. Herein, candidate locations are identified to cultivate Jatropha using the best-worst method and geographical information system. Moreover, the supply chain network is designed to optimize economic performance, network non-resiliency, and social impacts. The Monte Carlo simulation approach, k-means clustering, augmented epsilon constraint, and Mulvey robust optimization are adopted to generate and reduce probable scenarios, manage multiple objectives, and handle uncertainty, respectively. The results showed that the non-resilient supply chain experiences a 20.11% additional cost in disruption scenarios; however, even with a higher initial cost, adopting resiliency strategies reduces disruption cost effects by 9.46%. Managerial insights have demonstrated that resilience and sustainability are positively correlated in biofuel supply chain management, and rising biodiesel demand enhances social welfare and economic performance.