Disruptive Event

Disruptive events, encompassing supply chain failures, transportation network outages, and social unrest, are a major focus of current research aiming to improve prediction, mitigation, and response strategies. Studies employ diverse approaches, including machine learning models (e.g., deep learning architectures, tree-based algorithms, and reinforcement learning) and novel data sources (e.g., social media, satellite imagery, and multimodal transportation data) to analyze and forecast these events. This research is crucial for enhancing resilience in various sectors, from logistics and transportation to public safety and economic stability, by enabling proactive measures and optimized resource allocation during crises.