Automating the Analysis of Simulation Output Data
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Professor Stewart Robinson, Dr Katy Hoad, Professor Ruth Davies
Figure 1: Overview of the Automated Analysis Procedure Appropriate use of a simulation model requires accurate measures of model performance. This in turn, requires decisions concerning three key areas: warm-up, run-length and number of replications. Simulation software, however, gives little or no guidance in making these decisions. A three year project, "Automatic Simulation Output Analysis", sponsored by the EPSRC (Grant ref: EP/D033640/1) and SIMUL8 and undertaken by Warwick Business School , is investigating the development of a methodology for automatically advising a simulation user on these three decisions. This web site outlines the approach being taken, discusses progress to-date and provides links for research outputs. Obtaining Accurate Simulation ResultsEven with the best constructed simulation model if it is not used properly it is likely that the results will be inaccurate. If the results from a simulation of a system are not accurate they will not provide a good prediction of what would happen in the real life system even if the model itself is valid. The results could be biased and misleading, with the consequence that incorrect conclusions could be drawn. There are many decisions that need to be made about how a simulation model is to be run. These include:
In particular, the decisions on run-length, number of replications to perform in a trial and warm-up period require specific skills in statistics. Because of the variety and complexity of statistical methods used to make informed decisions on these matters, at the moment, most simulation software provide little or no guidance to users on making these important decisions. Because the setting of inappropriate run-lengths, run (replication) numbers and warm-up periods can lead to inaccurate and misleading results, it is considered important to deliver tools to simulation users that allow them to make informed decisions regarding these matters, whatever their statistical background. It is with this in mind that Warwick Business School and SIMUL8 have collaborated on a project to create an automated tool that can analyse preliminary simulation output and hence provide recommendations on warm-up, run-length and number of replications. Refs:
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Project PersonnelPrincipal Web Site editor & Research Fellow: Dr Katy Hoad Warwick Business School
University of Warwick
Coventry
CV4 7AL
UK
Contact e-mail: kathryn.hoad@wbs.ac.uk Principal Investigator: Professor Stewart Robinson
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