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

Our last paper at the Annual Modeling and Simulation Conference (ANNSIM) is entitled "Simulation and Optimization Techniques for the Mitigation of Disruptions to Supply Chains" where we (Raj Patel, Abhisekh Rana, Sean Luke, Carlotta Domeniconi, Hamdi Kavak, Jim Jones and myself) build upon our previous work which explored how the actions of criminal networks and agents might impact supply chains. 

 

This paper extends this research to incorporate both disruption and mitigation modeling into the same simulation.  By using evolutionary computation optimization techniques (e.g., Covariance Matrix Adaptation Evolution Strategy) we demonstrate how we can optimize both the disruption and mitigation scenarios in a pharmaceutical supply chain (which we call PharmaSIM). Our results demonstrate how  evolutionary computation techniques could be used to not only identify worst-case disruption scenarios but to also optimize the allocation of the mitigations to counter their effects.  If this sounds of interest, below we provide the abstract to the paper, some of the figures we use to support our discussion and results. While at the bottom of the post we provide the full reference to the paper along with a link to a preprint of it. 

Abstract

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.

Keywords: Simulation, Optimization, Supply Chains, Disruptions, Mitigation. 

Topology of the generic pharmaceutical supply chain (PharmaSIM) model.

Fitness after evolutionary optimization of attack configurations and corresponding safety stock allocation for different budgets.

Fitness by generation for the coevolution of attack vectors and mitigation configurations.

Full Reference:

Rana, R., Patel, R., Luke, S., Domeniconi, C., Kavak, H., Jones, J. and Crooks, A.T.  (2023), Simulation And Optimization Techniques for the Mitigation of Disruptions to Supply Chains, The Annual Modeling and Simulation Conference (ANNSIM), Hamilton, ON. (pdf)