DSI-625 Risk Simulation and Queuing

This course covers important modeling techniques. Students will learn how to construct and implement simulation models to model the uncertainty in decision input variables so that the overall estimate of interest from a model can be supplemented by a risk interval of possible other outcomes (risk simulation) and the variability in arrivals over time (customers, cars at a toll plaza, data packets, etc.) and ensuing queues (queuing theory). Students will also learn how to employ decision trees to incorporate information derived from models to actually make optimal decisions. Students will use spreadsheet-based software to specify and implement models. Graduate students enrolled in this course will complete a project/assignment that engages in higher levels of thought and creativity, requiring them to demonstrate knowledge at more advanced taxonomical levels.

Credits: 3

Offered in Nov 2020, May 2021

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