Currently, cyclic data cannot be input directly into AutoSimOA.
The cycle would
need to be taken out of the data by averaging over the cyclic periods.
Also, the Warm-
up Calculator cannot currently detect the initial bias in transient data.
Warm-up
methods assume steady-state and the question of initial bias in transient data has not
yet been adequately addressed in the research literature.
This work has concentrated on estimating the mean and variance of output data.
There are however other measures of performance that may be of interest to the user
37

e.g. proportions, quantiles…
It would be useful to extend AutoSimOA to provide
decisions for these measures.
8
CONCLUSION
An automated simulation output analyser, AutoSimOA, has been created in order to
estimate the mean and variance of output data.
The main components of AutoSimOA
analyse and advise on the warm-up period and number of replications or run-length
that should be used.
The completed analyser has been demonstrated with case studies using transient and
steady-state data, and has been shown to run smoothly and robustly.
38

39
NO
MODEL
Transient
Steady
State
Deterministic
Stochastic
Warm-up
Replications /
One long run
Warm-up
Batch Cycles
WHAT?
Transient
Steady
State
One long run
WARM-UP?
CYCLE?
WARM-UP?
CYCLE?
YES
NO
YES
NO
YES
NO
YES
NO
YES
YES
NO
WARM-UP?
WARM-UP?
YES
YES
NO
WARM-UP?
WARM-UP?
Replications
Batch Cycles
Warm-up
Warm-up
Warm-up
Batch Cycles
Batch Cycles
Warm-up
HOW?
Figure 20: The output analysis decision process.
NO

ACKNOWLEDGEMENTS
This work was part of the Automating Simulation Output Analysis (AutoSimOA)
project (
) that was funded by the UK Engineering and
Physical Sciences Research Council (EP/D033640/1).
The work was carried out in
collaboration with SIMUL8 Corporation, who also provided sponsorship for the
project.
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Alexopoulos, C., Fishman, G.S. and Seila, A.F. 1997
Computational Experience with
the Batch Means Method?"
Proceedings of the Winter Simulation Conference,
p194-201
Alexopoulos, C. (2006) A comprehensive review of methods for simulation output
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Banks, J., Carson II, J.S., Nelson, B.L., Nicol, D.M. (2005). Discrete-Event System
Simulation. 4
th
Edition. Prentice Hall, Upper Saddle River, NJ.
Bischak, D.P., Kelton, W.D. and Pollock, S.M. (1993) Weighted Batch Means for
Confidence Intervals in Steady-State Simulations
Management Science, Vol. 39,
No.8, p1002-1019.
Chen, E.J. and Kelton, W.D. (2007) A Procedure for Generating Batch-Means
Confidence Intervals for Simulation: Checking Independence and Normality
Chow YS, Robbins H (1965). On the asymptotic theory of fixed-width sequential
confidence intervals for the mean. The Annals of Mathematical Statistics; 36:
457-462.
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40

Delaney, P.J. 1995.
Control of initialisation bias in queuing simulations using queuing
approximations
. M.S. thesis, Department of Systems Engineering, University of
Virginia.

