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Building and operating resilient transportation yards using simulation

By Hafsa Mohsin, Jae Lee, Vamshi Suvarna
2023
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Developing a comprehensive model is a practical approach for gaining insight into and analyzing complex systems such as transportation yards. Following this approach, we have developed a data-driven agentbased model for transportation yards at Amazon which captures the features and processes of yard operations. By simulating different scenarios and using simulation performance indicators such as yard/parking slip/dock door utilization, entry/exit gate queue, and late departure counts, the model helps to identify potential bottlenecks, inefficiencies, and risks in the system. Moreover, the model provides customers with recommendations for achieving maximum daily volume using what-if scenarios. The model's accuracy is evaluated using mean absolute error (MAE) and root mean squared error (RMSE), yielding promising results of 6 % and 7 % respectively. This paper presents an overview of the model, current use cases, and outlines future works to further improve the simulation model and enhance yard operations.
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