Ambulance Dispatch Queue Deep Modeling: An Operations Research, Spatial Simulation, and Machine Learning Pipeline

This presentation outlines an end-to-end framework designed to overcome the limitations of classical queueing models (M/M/c) in emergency medical logistics. Because ambulance travel times depend strictly on spatial distance, traffic conditions, and spatial server coupling, standard closed-form equations fail to meet high-priority tail-risk performance standards (such as reaching 90%+ Advanced Life Support response within 8 minutes).

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