An Integrated Algorithmic and Learning-Assisted Framework for Decision-Making in Warehouse Digital Twins
Kerem Dogan
Modern robotic warehouse systems operate in dynamic and disruption-prone environments where maintaining connectivity is essential for operational continuity. While Digital Twin (DT) technology has emerged as a promising paradigm for monitoring and analysis of cyber-physical systems, many existing implementations remain limited to passive observation and lack integrated decision-support capabilities. In particular, selecting effective bypass actions under structural disruptions, where multiple fe