A hybrid simulation methodology for identifying and mitigating supply chain disruptions

Durring times of crisis, shocks to supply chains can propagate through the entire economy (e.g., global shortages of critical goods, such as personal protective equipment during COVID-19). At the same time, criminal organizations may disrupt and manipulate licit supply chains for financial gain or political objectives.  Thus there is a strong need for modeling and simulating not only supply chain operations but also malicious actors who may act to disrupt them. 

To explore this we (Abhisekh Rana, Raj Patel, Aman Goswami, Sean Luke, Alok Baveja, Carlotta Domeniconi, Benjamin Melamed, Fred Roberts, Weiwei Chen, Vladimir Menkov, Viswanath Narayan, James Jones, Hamdi Kavak and myself) have a new paper entitled  "Hybrid simulation methodology for identifying and mitigating supply chain disruptions" which was recently published in the Journal of Simulation. 

In the paper we introduce a novel hybrid modeling framework (implemented in MASON) designed to identify vulnerabilities across supply networks. Through the framework, we are able to analyze disruption scenarios  and evaluate mitigation strategies using a pharmaceutical supply chain model (i.e., PharmaSim). As such this paper and proposed framework provides a foundation for simulation-driven planning tools that help organizations anticipate risks and strengthen supply chain resilience.

If this sounds of interest, below we provide the abstract to the paper, some of the figures which show the supply chain we model and the simulation framework along with some results. While at the bottom of the page, you can find the full referece to the paper and a link to it, while the model itself is available at https://github.com/eclab/DES-Supply-Chain-demo. 

Abstract

Global disruptions have shown that shocks to supply chains can quickly ripple through entire economies, highlighting the need to identify vulnerabilities and evaluate mitigation strategies to build resilience. In this paper, we propose a simulation methodology, Hybrid Integrated Supply-Chain Simulation (HISS), to identify and mitigate potential disruptions in supply chains. We demonstrate HISS using a generic pharmaceutical supply chain model including sourcing, outsourcing, production, packaging, and distribution processes, created using MASON’s hybrid modeling capabilities. We classify disruptions from malicious actors and analyze their timing, impact, and scope. The simulation is further extended to modeling mitigation strategies and assessing their efficacy. Extensive optimization allowed us to identify worst-case disruptions and optimized safety stock strategies reduced impacts by a factor of five, while anomaly detection achieved a high recall of 0.966. The modeling approach proposed in this paper provides a basis for planning tools that support resilience and preparedness of supply chains.

Keywords: Hybrid simulation, supply chains modeling, resilience, optimization, evolutionary computation. 

Visual representation of pharmaceutical supply chain (PSC), which was used to code PharmaSim

Time series of daily production flow through the active pharmaceutical ingredient (API) Production node (resilience triangles are shown in red and the number of units on the vertical axis is in millions).

Overview of the software components and their interactions.

Sample time series of numbers of packaged units with anomalies due to (left) a disruption and due to (right) normal fluctuations (the number of units on the vertical axis is in millions).

Full reference:

Rana, A., Patel, R., Goswami, A., Luke, S., Baveja, A., Domeniconi, C., Melamed, B., Roberts, F., Chen, W., Crooks, A.T., Menkov, V., Narayan, V., Jones, J. and Kavak, H. (2026). A hybrid simulation methodology for identifying and mitigating supply chain disruptions. Journal of Simulation, 1–22. https://doi.org/10.1080/17477778.2026.2628944 (pdf)