Abstract

The COVID-19 pandemic has tested the resilience of Supply Chains (SCs), which has faced many restrictions and affected their global response. Worldwide stockouts were witnessed due to SCs disruptions, which may endanger lives since some products are critical to responding to this global threat, such as ventilators and Personal Protective Equipment (PPE). Thus, this work aims to help deal with the pandemic impacts on critical SCs, addressing the distribution of materials that are used to cope with the pandemic and considering the resilience of its SCs, dealing with a gap of few studies combining simulation and optimization approaches to tackle this situation. We propose a dynamic framework based on a stochastic population model to address pandemic behavior and an optimization model to support decision-making in a PPE supply chain subject to a pandemic-driven disruption that can be updated anytime necessary. We develop a social objective function that aims to deliver PPE where they are most needed. The proposed approach is illustrated by an example involving real data from a Brazilian company that distributes PPE during the COVID-19 pandemic. We find that profit was inversely correlated with social gain, suggesting that optimizing profits is a poor strategy for addressing public health or social crisis. Still, our model furnishes results with an acceptable profit while prioritizing its effect on coping with the pandemic. As implications, our framework can be applied to support decision makers to improve SCs’ resilience and better allocate resources during disruptive circumstances in which the uncertainty is high, such as future pandemics.

Full Text
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