PPE Supply Optimization Under Risks of Disruption from the COVID-19 Pandemic

The COVID-19 pandemic has struck health service providers around the world with dire shortages, inflated prices, and volatile demand of personal protective equipment (PPE). This paper discusses supply chain resilience in context a Canadian provincial healthcare provider during pandemic. A multi-period multi-objective mixed-integer programming model is presented for PPE planning under disruption risk. deterministic formulation extended to consider both two-stage multi-stage uncertainty supply, price, using stochastic (SP) chance-constrained (CCP). first objective minimize risk measure total cost, either its Expected Value (EV) or Value-at-Risk (VaR), second maximum shortage any product time period. $$\epsilon$$ -constraint method used generate sets Pareto-optimal solutions analyze trade-off between these two competing objectives. Numerical experiments are conducted efficacy emergency inventory increased levels as mitigation strategies. We scenarios based on plausible actual trajectories seen including single-wave, two-wave, exponential growth.