Currently cyclic data cannot be input directly into AutoSimOA The cycle would

Currently cyclic data cannot be input directly into

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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
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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
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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
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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. REFERENCES 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 analysis. Proceedings of the 2006 Winter Simulation Conference, p168-178 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. Conway, R.W. (1963). Some technical problems in digital simulation. Management Science, 10 (1), 47-61. 40
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Delaney, P.J. 1995. Control of initialisation bias in queuing simulations using queuing approximations . M.S. thesis, Department of Systems Engineering, University of Virginia.
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