Adaptive resilience strategies for supply chain networks against disruptions

Supply chain networks face the critical challenge of enhancing resilience to disruptions while controlling the costs associated with resilience improvements. In this paper, we introduce an adaptive resilience improvement framework designed to sustain material flow by responding dynamically to emerging network vulnerabilities. Our framework centers on the production chain as a core element in resilience planning, integrating vulnerability assessment and reinforcement strategies through a tri-level optimization model. This model adapts to the network's changing conditions by (i) incorporating disruption scenario generation as an integral part of the decision-making process, allowing for the dynamic identification of vulnerabilities, and (ii) optimizing reinforcement strategies in response to them. We demonstrate the framework's effectiveness through two distinct case studies: a steel supply chain, where production flexibility improves resilience by 30%, and a pharmaceutical supply chain affected by climate-related disruptions. Our computational results confirm the scalability and effectiveness of this approach in strengthening network-wide resilience as vulnerabilities evolve.