Simulation output analysis: non-stationary queue simulation analysis using time series
Proceedings of the 35th conference on Winter simulation: driving innovation
Queueing network simulation analysis: queueing-network stability: simulation-based checking
Proceedings of the 35th conference on Winter simulation: driving innovation
Simulation output analysis: a tutorial based on one research thread
WSC '04 Proceedings of the 36th conference on Winter simulation
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
An analytical model for conveyor based amhs in semiconductor wafer fabs
Proceedings of the 40th Conference on Winter Simulation
Verification and validation of simulation models
Proceedings of the Winter Simulation Conference
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Modeling healthcare systems using discrete-event simulation (DES) provides the flexibility to analyze both their steady-state and transient performance. However, there has been little work on how best to measure healthcare system performance in cases where there is at least one unstable and lengthening queue in the system, so that traditional steady-state measures such as mean queue length or mean time in queue are meaningless. Using the example of an academic sleep disorders clinic, the authors discuss some of the challenges in constructing a DES model of a healthcare system that has a growing waiting list due to insufficient capacity in one or more areas. Specific considerations include: bottleneck identification through pre-analysis, how to determine a meaningful warm-up period, and the selection of performance measures given system instability.