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Controlled sequential factorial design for simulation factor screening


  • Shen, Hua
  • Wan, Hong


Screening experiments are performed to eliminate unimportant factors efficiently so that the remaining important factors can be studied more thoroughly in later experiments. This paper proposes controlled sequential factorial design (CSFD) for discrete-event simulation experiments. It combines a sequential hypothesis testing procedure with a traditional (fractional) factorial design to control the Type I error and power for each factor under heterogeneous variance conditions. We compare CSFD with other sequential screening methods with similar error control properties. CSFD requires few assumptions and demonstrates robust performance with different system conditions. The method is appropriate for systems with a moderate number of factors and large variances.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ejores:v:198:y:2009:i:2:p:511-519

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    References listed on IDEAS

    1. Bettonvil, Bert & Kleijnen, Jack P. C., 1997. "Searching for important factors in simulation models with many factors: Sequential bifurcation," European Journal of Operational Research, Elsevier, vol. 96(1), pages 180-194, January.
    2. Renata Kopach & Po-Ching DeLaurentis & Mark Lawley & Kumar Muthuraman & Leyla Ozsen & Ron Rardin & Hong Wan & Paul Intrevado & Xiuli Qu & Deanna Willis, 2007. "Effects of clinical characteristics on successful open access scheduling," Health Care Management Science, Springer, vol. 10(2), pages 111-124, June.
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    Cited by:

    1. repec:eee:ejores:v:262:y:2017:i:2:p:673-681 is not listed on IDEAS
    2. 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.
    3. 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.
    4. 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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