Simulation experiments


Simulation experiments can build on a simulation toolbox, such as the ASM, to systematically investigate different configurations of a model (eg. a process model) and identify those configurations which create desirable combinations of performance variables.

To prepare a model to run simulation experiments

A model must be appropriately configured to run simulation experiments. Essentuially, the model must be configured to denote certain variables as inputs `Independent variables` and others as outputs `Dependent variables`. The model is then treated as a black box in which the inputs can be varied to determine the effect on the outputs.

  1. Create a simulation model, eg. using the ASM toolbox
  2. Identify the independent variables - ie. things that could be changed to alter the system behaviour. (these might, for instance, include numbers of iterations for an ASM process simulation). Use CAM variables to represent these, and in the "Variable properties" dialog, under the "Experimentation" tab, ensure that the "Independent variable" option is ticked.
  3. Define the behaviour of the model in terms of those variables, eg. using task properties dialog in an ASM model.
  4. Identify the dependent variables - ie. things that measure the performance of the system. For instance, cost of the process. In the "Variable properties" dialog, under the "Experimentation" tab, ensure that the "Dependent variable" option is ticked.
  5. Write the dependent variables into the simulation model, so that their final values are set by the end of each simulation run to measure the 'performance' of that run.

To configure and run the experiments

  1. Use the "Simulation experiment" option under the "analysis" menu of the main CAM application menu bar to configure and run a simulation experiment. You can choose between a full-factorial design (in which all independent variables are varied in a certain number of steps within a given range) or you can upload a custom design from Excel.
  2. Results are created as a special kind of dataset, and displayed by default as a parallel co-ordinate chart
  3. Use the 'Selection' sliders on each of the parallel co-ordinate axes to explore the dataset visually, or for other visualisations of the results, use the inbuilt charting functionality.<
  4. You can easily export the results to Excel using the CSV button on the top toolbar of the parallel co-ordinate chart.


See also

Setting up CAM for distributed computing