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The Arena model has been designed to simulate the workflow of the emergency room as accurately as possible. It has one top-level model and two sub-models.
Create Models
In our Arena model, there are three create modules representing patients arrival. The patients' arrivals follow an exponential distribution as following: patients with ambulance cars expo (55), patients with their own cars expo (30), and exceptional-patients search entity constant (1).
We have assigned four assign modules for the three create modules. The first assign module has three attributes: one for the system time (TNOW), another for the first patient type (myType1), and the third for the priority. The second assign module is specified for the second type of patient which has two priorities: high and low. It has three attributes: one for the system time, another for the second patient time with distribution located in the expression spreadsheet, and the third attribute for the priority. In addition, there are two others located in the set, one for the two priorities and the other for their pictures. The third assign module has only the system time attribute and belongs to the entity that searches for exceptional patients. Finally, the last assign module assigns the patients who have been removed from the urgent doctor queue, and it has three attributes.
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Input Data Collection The input data for the model was collected accurately to be as close as possible to a typical emergency room. We expected that the number of patients comi
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