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Controlled Sequential Bifurcation: A New Factor-Screening Method for Discrete-Event Simulation

Author

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  • Hong Wan

    (School of Industrial Engineering, Purdue University, West Lafayette, Indiana 47907-2023)

  • Bruce E. Ankenman

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208-3119)

  • Barry L. Nelson

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208-3119)

Abstract

Screening experiments are performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Sequential bifurcation (SB) is a recent screening method that is well suited for simulation experiments; the challenge is to prove the “correctness” of the results. This paper proposes controlled sequential bifurcation, a procedure that incorporates a hypothesis-testing approach into SB to control error and power. A detailed algorithm is given, conditions that guarantee performance are provided, and an empirical evaluation is presented.

Suggested Citation

  • Hong Wan & Bruce E. Ankenman & Barry L. Nelson, 2006. "Controlled Sequential Bifurcation: A New Factor-Screening Method for Discrete-Event Simulation," Operations Research, INFORMS, vol. 54(4), pages 743-755, August.
    • Handle: RePEc:inm:oropre:v:54:y:2006:i:4:p:743-755
    DOI: 10.1287/opre.1060.0311
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    References listed on IDEAS

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    Cited by:

    1. Shi, Wen & Chen, Ao & Xie, Xiang, 2024. "Generating and validating cluster sampling matrices for model-free factor screening," European Journal of Operational Research, Elsevier, vol. 313(1), pages 241-257.
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    3. 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.
    4. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    5. Nicola Rossi & Mario Bačić & Lovorka Librić & Meho Saša Kovačević, 2023. "Methodology for Identification of the Key Levee Parameters for Limit-State Analyses Based on Sequential Bifurcation," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    6. Shi, Wen & Chen, Xi, 2019. "Controlled Morris method: A new factor screening approach empowered by a distribution-free sequential multiple testing procedure," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 299-314.
    7. Hong Wan & Bruce E. Ankenman & Barry L. Nelson, 2010. "Improving the Efficiency and Efficacy of Controlled Sequential Bifurcation for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 22(3), pages 482-492, August.
    8. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    9. 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.
    10. Regine Pei Tze Oh & Susan M. Sanchez & Thomas W. Lucas & Hong Wan & Mark E. Nissen, 2009. "Efficient experimental design tools for exploring large simulation models," Computational and Mathematical Organization Theory, Springer, vol. 15(3), pages 237-257, September.
    11. E. Borgonovo & C. L. Smith, 2011. "A Study of Interactions in the Risk Assessment of Complex Engineering Systems: An Application to Space PSA," Operations Research, INFORMS, vol. 59(6), pages 1461-1476, December.
    12. Shen, Hua & Wan, Hong, 2009. "Controlled sequential factorial design for simulation factor screening," European Journal of Operational Research, Elsevier, vol. 198(2), pages 511-519, October.
    13. Wen Shi & Xi Chen, 2018. "Efficient budget allocation strategies for elementary effects method in stochastic simulation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(3), pages 218-241, April.
    14. Shi, Wen & Liu, Zhixue & Shang, Jennifer & Cui, Yujia, 2013. "Multi-criteria robust design of a JIT-based cross-docking distribution center for an auto parts supply chain," European Journal of Operational Research, Elsevier, vol. 229(3), pages 695-706.
    15. Kleijnen, J.P.C., 2007. "Screening Experiments for Simulation : A Review," Discussion Paper 2007-21, Tilburg University, Center for Economic Research.
    16. Besseris, George J., 2012. "Profiling effects in industrial data mining by non-parametric DOE methods: An application on screening checkweighing systems in packaging operations," European Journal of Operational Research, Elsevier, vol. 220(1), pages 147-161.

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