Simulation and Optimization Techniques for the Mitigation of Disruptions to Supply Chains

The COVID-19 pandemic has clearly highlighted the importance of supply chains to the function of the world economy. Moreover, the global nature of most modern supply chains along with their complexity has left them vulnerable to a wide-ranging set of disruptive scenarios. This increase in complexity has also led to a corresponding increase in disruptions to supply chains from criminal networks. In this paper, we demonstrate how a generic pharmaceutical supply chain network can be successfully modeled using discrete event simulation. We outline how disruptions by criminal networks and mitigation strategies to counter them can be effectively incorporated into the same model. Finally, we show how optimization techniques, such as evolutionary computation, can be used to not only identify worst-case disruptions and find mitigations for them, but also be used to identify mitigation strategies that are effective against a diverse set of damaging disruption scenarios.