Queues or waiting lines are a fact of life for the service and manufacturing industries. Analyzing a queue to establish operating characteristics (e.g., average wait time) provides critical metrics to staffing, layout, and other important decisions. Relying on the analytical approach (e.g., M/M/1 equations) taught in most introductory courses in operations research or management science however involves accepting often-unrealistic assumptions (e.g., no balking allowed). Simulation is appropriate when the queue being analyzed deviates from these assumptions. Specialized simulation software exists for this purpose, but it can be pricey. When combined with Excel, @RISK provides a flexible alternative.
Following a brief discussion of basic queueing concepts and the analytically based operating characteristics equations, this webinar will present an Excel model that when combined with @RISK can be used to simulate a single-server queue. After demonstrating how the initial simulation model yields results equivalent to the analytical approach, several embellishments will be made to account for situations where the restrictive assumptions don’t hold.