Ventana software support forum

Greetings!

In the simple discrete model (attached) of a queue, I would like to find the average cycle time it takes for a customer to get service (problem taken from Chapter 4, Modeling Dynamic Economic Systems by Bruce Hannon).

In Stella, this is done simply by creating using a built in function though, I believe that (according to Professor Sterman's book) one should track attributes by creating coflows.

I have created a coflow but it is not giving me the correct results, at least I don't think so; does anyone have any suggestions as to how I should proceed? I presume it doesn't matter that my input is in discrete intervals.

The general formulation for average residence time in a continuous model is

average residence time = level / outflow

That this makes sense is clear from the standard formulation

outflow = level / average residence time

That assumes an exponential distribution of service times. If you want to assume something different, for example a fifo queue, then you need to make use of the QUEUE functions to get a more accurate result. But the above is usually good enough.

Thank you very much Bob! However, I believe that the QUEUE functions are not available to PLE users; Do you perhaps have a coflow structure suggestion/solution for me?

Just go with the above solution and an exponential distribution of service times. If you want to use a cascaded chain then you can use

service time = service time 1 + service time 2 + service time 3

where

service time 1 = level 1 / outflow 1

and so on. As you add more levels you will approach a FIFO service time.