Simulation output

Output data from the Anylogic simulation model used for training machine learning models in Ashraf, M., Eltawil, A., & Ali, I. (2024). Disruption detection for a cognitive digital supply chain twin using hybrid deep learning. Operational Research, 24(2), 23. https://doi.org/10.1007/s12351-024-00831-y. Each file contains relevant replications under a particular scenario. Each file contains the observed daily values for each feature in the form of (timestamp(day), value) pairs. The features are: MeanInterarrivalTime, MeanSupplierProcessingTime, MeanManufacturerProcessingTime, MeanDisributorProcessingTime, SupplierUtilizationFactor, ManufacturerUtilizationFactor, DistributorUtilizationFactor, MeanSupplierQueueLength, MeanManufacturerQueueLength, MeanDistributorQueueLength, MeanBacklog, MeanWorkInProcess, MeanLeadTime, MeanFlowTime, MeanWaitingTime, MeanProcessingTime, and DailyOutput. For disrupted scenarios, disruption end time stamp as well as disruption impact start and end timestamps are included for each replication.