Resilience of global supply chains with logistics service uncertainty: Onshoring versus offshoring strategy

Supply chain resilience aims to enhance supply chain's capacity to resist, respond, and recover from the disruptions. In different industries, products exhibit distinct attributes, such as, product value, deterioration rate, and criticality, resulting in varied resilience performance under logistic disruptions. The goal of this study is to investigate the significance of logistics service network in enhancing resilience within different supply chain typologies (onshoring and offshoring) across diverse industries, in face to transit time uncertainty induced by disruptions. We develop a robust optimization model with budgeted uncertainty to address the involved single-commodity multimodal freight routing problem under transit time uncertainty. To manage real-world large-scale instances, we devised a tailored adaptive large neighborhood search algorithm and validated its performance by computational experiments. Furthermore, we conducted realistic numerical experiments to validate the proposed approach, and sensitivity analyses to assess supply chain resilience from two perspectives: supply chain typologies and industry-specific attributes including product value, deterioration, and criticality. Moreover, the dynamics of modal shift under various disruptions were also analyzed. The study aims to provide practical tools and managerial insights to help industrial practitioners improve the resilience of their logistics service networks and emphasizes the importance of industry-specific considerations of supply chain typology in enhancing resilience.