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Proceedings Paper

Optimal way to find the optimal design for discrete-event stimulation experiments
Author(s): Chun-Hung Chen; Liyi Dai; Enver Yucesan
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Paper Abstract

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.

Paper Details

Date Published: 24 August 1998
PDF: 11 pages
Proc. SPIE 3369, Enabling Technology for Simulation Science II, (24 August 1998); doi: 10.1117/12.319339
Show Author Affiliations
Chun-Hung Chen, Univ. of Pennsylvania (United States)
Liyi Dai, Washington Univ. (United States)
Enver Yucesan, Univ. of Pennsylvania (France)


Published in SPIE Proceedings Vol. 3369:
Enabling Technology for Simulation Science II
Alex F. Sisti, Editor(s)

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