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A hybrid simulation methodology for identifying and mitigating supply chain disruptions

  • Abhisekh Rana
  • , Raj Patel
  • , Aman Goswami
  • , Sean Luke
  • , Alok Baveja
  • , Carlotta Domeniconi
  • , Benjamin Melamed
  • , Fred Roberts
  • , Weiwei Chen
  • , Andrew Crooks
  • , Vladimir Menkov
  • , Viswanath Narayan
  • , James Jones
  • , Hamdi Kavak
  • George Mason University
  • Rutgers - The State University of New Jersey, New Brunswick
  • Retired Pharmaceutical Executive

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
JournalJournal of Simulation
DOIs
StateAccepted/In press - 2026

Keywords

  • evolutionary computation
  • Hybrid simulation
  • optimisation
  • resilience
  • supply chains modelling

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