Abstract
Factor screening means searching for the most important factors (or inputs) among the many factors that may be varied in an experiment with a real or a simulated system. This chapter gives a review of Sequential Bifurcation (SB), which is a screening method for simulation experiments in which many factors may be varied. SB is most efficient and effective if its assumptions are satisfied. SB was originally studied back in 1990. This review first summarizes SB. Then it summarizes a recent case study, namely, a supply-chain simulation with 92 factors where SB identifies a shortlist with 10 factors after simulating only 19 combinations. The review also references recent research. It ends with a discussion of possible topics for future research.
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Acknowledgements
I thank Bert Bettonvil and Wim van Beers (both at Tilburg University) for their comments on an earlier version.
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Kleijnen, J.P. (2009). Factor Screening in Simulation Experiments: Review of Sequential Bifurcation. In: Alexopoulos, C., Goldsman, D., Wilson, J. (eds) Advancing the Frontiers of Simulation. International Series in Operations Research & Management Science, vol 133. Springer, Boston, MA. https://doi.org/10.1007/b110059_8
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