Simulation-based Predictive Analytics for Dynamic Queueing Systems
Published in 2017 Winter Simulation Conference (WSC), 1716–1727, 2017
We develop a two-step method to dynamically predict congestion measures in queueing systems using sample paths from detailed simulations.
This paper was presented at the 2017 Winter Simulation Conference (WSC) and focuses on predictive analytics for dynamic queueing systems. The research introduces a novel method to dynamically predict the probability of system states based on simulation data, demonstrating its effectiveness on two examples.
Recommended citation: Huiyin Ouyang and Barry L. Nelson (2017). "Simulation-based Predictive Analytics for Dynamic Queueing Systems." 2017 Winter Simulation Conference (WSC), 1716–1727. https://doi.org/10.1109/WSC.2017.8247910
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