Modeling Risk Propagation and Resilience in Logistics Networks

A growing variety of linked hazards including climatic disasters, cyberattacks, and supply chain disruptions logistics networks are becoming more susceptible to them. Maintaining operational continuity now depends on knowing how these hazards spread throughout intricate logistic systems and how resilience may be strengthened. This study presents a dynamic modelling method inspired by epidemic models (SEIQR) to grasp the processes of risk distribution and resilience development within transport logistics systems. Representing logistic hubs or infrastructures, nodes in the network go through several stages (Susceptible, Exposed, Infected, Quarantined, Recovered) depending on the development of risk exposure and resilience treatments. The suggested model provides a flexible framework to direct decision-makers in constructing smarter, more resilient logistic systems by measuring the interaction between risk propagation and resilience solutions. Aiming to assist risk-informed planning and adaptive logistics network design, Future work will aim to deepen the research through extended simulations and the analysis of complex scenarios based on real-world data.