Classification of DES Models and their output data

The following model and output data characteristics are used in this project to sufficiently describe and categorise a representative set of artificial and "real" discrete event simulation models and their output.

Model characteristics	Output data characteristics
Deterministic or stochastic Significant pre-determined model changes (by time) Dynamic internal changes i.e. ‘feed-back’	Empty-to-empty pattern Initial transient (warm-up) Out of control trend ρ≥1 Cycle Auto-correlation Statistical distribution

It is thought desirable to collect an example of every significantly different type of model/output according to the above criteria.

The gathered set of models and data sets will be used to:

Provide a representative and sufficient set of models / data output for use in discrete event simulation research.
Test the chosen simulation output analysis methods in the AutoSimOA Project
- To determine the effectiveness of the analysis methods (warm-up, replication number, run length).
- To revise the methods where necessary in order to improve their effectiveness and capacity for automation.

For a more comprehensive description and explanation of the classification of models and output carried out at the start of this project please click here (or on the link at the top left of this page - Model output classification)... And to view the complete classification tables please click on: table for steady state output; table for transient ouput. The data (artificial and 'real' models) that have been used in this research project can be downloaded from the 'Data for download' page on this web site.

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