An optimization approach for sustainable and resilient supply chain design with regional considerations

Abstract

Regional and geographical differences between facilities is of paramount importance in supply chain design. However, the impact of the regions' performance on supply chain design decisions remains a relatively under-researched subject in the literature. This paper presents a hybrid methodology for designing a sustainable supply chain that is resilient to random disruptions. We propose a multi-period multi-objective optimization model that utilizes a k-means clustering method to evaluate the regions' sustainability performance. The model aims to determine sourcing and network design decisions as well as resilience strategies. To manage the operational risks associated with the supply chain, we employ a new robustness measure that eliminates the need to estimate the probability distribution of random parameters. Finally, a Benders decomposition algorithm is developed to solve the model. Practical insights are drawn from an actual case study of a downstream petrochemical industry in Iran.