This is a common class of problem that arises in many domains - the workload
in a machine shop is but one of many cases. It is usually addressed, as you
have done, by discrete event simulation (DES) using any one of a number of
DES languages. (CSL was a good one but Im not sure what is now available).
The usual output is a distribution of such variables as queue length at a
work station, time to go through the system etc. The characteristics of that
distribution, such as its mean, mode, variance, probability that a given
value will be exceeded, and its shape are indicators of the relative
merits of different operating rules. For example, in a machine shop (which
is a case I have dealt with) is it better to take the largest job first, the
smallest first, the one that has waited longest, or whatever? The other
input is, of course, the numbers of machines at each manufacturing stage,
size of storage areas etc. All these can be taken into the simulation to see
that happens to the distribution. It would be unusual to be interested in
the time profile of, say, queue length; what normally matters is the nature
of the performance over some period of time, as measured by the
For your TTTA problem, you seem to be on the right track with distributions
of patient needs and arrivals and your two decision rules on patient
allocations. Other factors are, of course, the numbers of doctors (and
nurses) available, the size of the facility in terms of consulting rooms and
beds, the capacity of the support services such as patient records and no
doubt other factors. You could simulate this over a year, say, to allow for
winter epidemics and so forth. You could even separate out the different
seasons and look at how the numbers of available resources might need to
vary over the year.
Im not at all sure that SD is an appropriate methodology for this class of
problem and Id be interested in knowing why you think that it is. Of
course, SD is great for all sorts of problems and it is not hard to
represent discrete events within an SD model, when it is appropriate to do
so (see the literature) but SD does not do everything and I always urge
students (force is closer to it) to justify the choice of a methodology with
respect to the type of problem being addressed.
I hope that helps.
From: "geoff coyle" <firstname.lastname@example.org>
Professor Geoff Coyle
Visiting Professor of Strategic Analysis, University of Bath.
Telephone 44 (0) 1793 782817
Fax 44 (0) 1793 783188