Simulation Modeling and Analysis
Simulation Modeling and Analysis
Averages kill: (or how to sell business process simulation)
Proceedings of the 33nd conference on Winter simulation
Making simulation relevant in business: achieving higher levels of CMMI maturity using simulation
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Spreadsheet simulation: spreadsheet simulation
Proceedings of the 35th conference on Winter simulation: driving innovation
Emergency departments II: simulating Six Sigma improvement ideas for a hospital emergency department
Proceedings of the 35th conference on Winter simulation: driving innovation
Using RFID technologies to capture simulation data in a hospital emergency department
Proceedings of the 38th conference on Winter simulation
Merging six emergency departments into one: a simulation approach
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Estimating patient surge impact on boarding time in several regional emergency departments
Winter Simulation Conference
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Effective simulation models require robust development methodologies. Planning, design, data, and testing are integral to ensure valuable answers to the model's customers. This paper discusses how supporting static models provide guidelines and directional correctness to simulation models. Static models can also provide supplemental answers which allow the reduction in simulation model complexity.