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Factor Screening in Simulation Experiments: Review of Sequential Bifurcation

In: Advancing the Frontiers of Simulation

Author

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  • Jack P. C. Kleijnen

    (Tilburg University)

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.

Suggested Citation

  • Jack P. C. Kleijnen, 2009. "Factor Screening in Simulation Experiments: Review of Sequential Bifurcation," International Series in Operations Research & Management Science, in: Christos Alexopoulos & David Goldsman & James R. Wilson (ed.), Advancing the Frontiers of Simulation, pages 153-167, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-0817-9_8
    DOI: 10.1007/b110059_8
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    Citations

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    Cited by:

    1. Shi, Wen & Kleijnen, Jack P.C. & Liu, Zhixue, 2014. "Factor screening for simulation with multiple responses: Sequential bifurcation," European Journal of Operational Research, Elsevier, vol. 237(1), pages 136-147.
    2. Aitor Iriondo Pascual & Henrik Smedberg & Dan Högberg & Anna Syberfeldt & Dan Lämkull, 2022. "Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    3. J P C Kleijnen & W C M van Beers, 2013. "Monotonicity-preserving bootstrapped Kriging metamodels for expensive simulations," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(5), pages 708-717, May.
    4. Ali K. Raz & C. Robert Kenley & Daniel A. DeLaurentis, 2018. "System architecting and design space characterization," Systems Engineering, John Wiley & Sons, vol. 21(3), pages 227-242, May.
    5. Shi, Wen & Shang, Jennifer & Liu, Zhixue & Zuo, Xiaolu, 2014. "Optimal design of the auto parts supply chain for JIT operations: Sequential bifurcation factor screening and multi-response surface methodology," European Journal of Operational Research, Elsevier, vol. 236(2), pages 664-676.
    6. Plischke, Elmar & Borgonovo, Emanuele & Smith, Curtis L., 2013. "Global sensitivity measures from given data," European Journal of Operational Research, Elsevier, vol. 226(3), pages 536-550.

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