Ventana software support forum

Aitor,

Please correct me if Im wrong, but I think that...

There is a difference in practice in that System Dynamics Models are almost
always centrally interested in feedback processes. In contrast discrete
event models are almost always centrally concerned with impact of stochastic
processes on things like though-put, lines and waiting times.

Also in practice, system dynamics models are usually at a managerial level
looking at things like pricing policies or company expansion or hiring and
firing, while discrete event models are often focussed at a "shop-floor"
level on things like machine placement or the progress of packages through a
transport system.

On a technical level, I think that analyzing feedback is easier in SD models
where "events" usually are continuous (i.e. the variables tracking events
are continuous). Discrete event models present simulation results in terms
of statistics (e.g. average throughput); whereas SD models present output as
plots of the continuous curves - a format that is well suited for seeing
behavior patterns and finding the causal loops responsible.

Finally on a model level, I think that discrete-event models are often more
intuitive, because the model actually represents concrete items like an
individual machine , separate packages, or a single person. System dynamics
models use a lot of aggregation (e.g. a number representing the level of
inventory instead of the individual items in the inventory) which SDers
eventually come to see as being, but which I think is actually a bit more
abstract.

On a theoretical level, I dont see any reason that you couldnt use
discrete event tools to examine some (and perhaps most) feedback issues; and
I know that system dynamics tools like iThink are frequently used to model
the impact of stochastic processes on lines and waiting times.

Regards,
Jim Hines JHines@mit.edu