24 August 1998 Optimal way to find the optimal design for discrete-event stimulation experiments
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Simulation plays a vital role in analyzing many discrete- event systems, particularly, in comparing alternative system designs with a view to optimize system performance. Usually, using simulation to analyze complex systems can be both prohibitively expensive and time consuming. We present an effective algorithm to intelligently allocate computing budget for discrete-event simulation experiments. These algorithms dynamically determine the best simulation lengths for all simulation experiments and thus significantly reduce the total computation cost for a desired confidence level. This provides an optimal way to find an optimal design. We also compare our algorithms with traditional two-stage procedures and with the techniques for the multi-armed bandit problem through numerical experiments. Numerical testing shows that our approach is more than fifteen times faster than the compared methods for the same simulation quality requirements.
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Chun-Hung Chen, Chun-Hung Chen, Liyi Dai, Liyi Dai, Enver Yucesan, Enver Yucesan, } "Optimal way to find the optimal design for discrete-event stimulation experiments", Proc. SPIE 3369, Enabling Technology for Simulation Science II, (24 August 1998); doi: 10.1117/12.319339; https://doi.org/10.1117/12.319339

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