40
2. Modeling in STELLA
The following section provides a set of guidelines designed to facilitate
model development and help you avoid some of the errors discussed
above . An important recommendation is to explore the sensitivity of model
results to different model specifications. Chapter 4 will take up the issue of
sensitivity analysis in more detail.
2.5. Guidelines for the Development
of a Dynamic Model
Before we move on to develop increasingly sophisticated models of dynamic systems, let us identify some general guidelines for such an endeavor. Those guidelines are particularly useful when developing the
model in STELLA, or any other easy-to-use programming language. When
the mod eling language is very easy to use, and additions to the model can
be don e quickly at very little cost, it is all too easy to get carried away with
one's modeling effort. If you keep adding extra features to a model without
keepin g a clear que stion for the model in mind, you can end up with a
model that is difficult to und erstand , or even useless in answe ring your
question. Remember that it is the very purpose of the model to abstract
from inessential details and to focus on the key parameters and relations
needed to generate new insight.
Discipline yourself in your modeling efforts and keep the following
guidelines for model development in mind:
1. Define the problem and the goals of the model. Frame the questions
you want to answer with the model. If the problem is a very large one,
define subsystems of it and goals for the modelin g of these subsystems.
Think now: Is my model to be descriptive or predictive?
2. Designate the state variables. (These variables will indicate the status
of the system.) Keep it simple. Purposely avoid complexity in the beginning. Note the units of the state variables.
3. Select the control variables, the flow controls into and out of the state
variables. (The control variables are calculated from the state variable in
order to update them at the end of each time step.) Note to yourself
which state variables are donors and which are recipients with regard
to each of the control variables. Also, note the units of the control variables. Keep it simple at the beginning. Try to capture only the essential
features. Put in one type of control as a representative of a class of similar controls. Add the others in step 10.
4. Select the parameters for the control variables. Note the units of these
parameters and control variables. Ask yourself: What are these controls
and their parameters a function of?
5. Examine the resulting model for possible violations of physical, economic, etc., laws; for example, the conservation of mass, energy and
2. Modeling in STELLA
The following section provides a set of guidelines designed to facilitate
model development and help you avoid some of the errors discussed
above . An important recommendation is to explore the sensitivity of model
results to different model specifications. Chapter 4 will take up the issue of
sensitivity analysis in more detail.
2.5. Guidelines for the Development
of a Dynamic Model
Before we move on to develop increasingly sophisticated models of dynamic systems, let us identify some general guidelines for such an endeavor. Those guidelines are particularly useful when developing the
model in STELLA, or any other easy-to-use programming language. When
the mod eling language is very easy to use, and additions to the model can
be don e quickly at very little cost, it is all too easy to get carried away with
one's modeling effort. If you keep adding extra features to a model without
keepin g a clear que stion for the model in mind, you can end up with a
model that is difficult to und erstand , or even useless in answe ring your
question. Remember that it is the very purpose of the model to abstract
from inessential details and to focus on the key parameters and relations
needed to generate new insight.
Discipline yourself in your modeling efforts and keep the following
guidelines for model development in mind:
1. Define the problem and the goals of the model. Frame the questions
you want to answer with the model. If the problem is a very large one,
define subsystems of it and goals for the modelin g of these subsystems.
Think now: Is my model to be descriptive or predictive?
2. Designate the state variables. (These variables will indicate the status
of the system.) Keep it simple. Purposely avoid complexity in the beginning. Note the units of the state variables.
3. Select the control variables, the flow controls into and out of the state
variables. (The control variables are calculated from the state variable in
order to update them at the end of each time step.) Note to yourself
which state variables are donors and which are recipients with regard
to each of the control variables. Also, note the units of the control variables. Keep it simple at the beginning. Try to capture only the essential
features. Put in one type of control as a representative of a class of similar controls. Add the others in step 10.
4. Select the parameters for the control variables. Note the units of these
parameters and control variables. Ask yourself: What are these controls
and their parameters a function of?
5. Examine the resulting model for possible violations of physical, economic, etc., laws; for example, the conservation of mass, energy and