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Factor Screening for Simulation with Multiple Responses : Sequential Bifurcation

Author

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  • Shi, W.
  • Kleijnen, Jack P.C.

    (Tilburg University, Center For Economic Research)

  • Liu, Zhixue

Abstract

The goal of factor screening is to find the really important inputs (factors) among the many inputs that may be changed in a realistic simulation experiment. A specific method is sequential bifurcation (SB), which is a sequential method that changes groups of inputs simultaneously. SB is most efficient and effective if the following assumptions are satisfied: (i) second-order polynomials are adequate approximations of the input/output functions implied by the simulation model; (ii) the signs of all first-order effects are known; and (iii) if two inputs have no important first-order effects, then they have no important second-order effects either (heredity property). This paper examines SB for random simulation with multiple responses (outputs), called multi-response SB (MSB). This MSB selects groups of inputs such that—within a group—all inputs have the same sign for a specific type of output, so no cancellation of first-order effects occurs. To obtain enough replicates (replications) for correctly classifying a group effect or an individual effect as being important or unimportant, MSB applies Wald’s sequential probability ratio test (SPRT). The initial number of replicates in this SPRT is also selected efficiently by MSB. Moreover, MSB includes a procedure to validate the three assumptions of MSB. The paper evaluates the performance of MSB through extensive Monte Carlo experiments that satisfy all MSB assumptions, and through a case study representing a logistic system in China; the results are very promising.
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Suggested Citation

  • Shi, W. & Kleijnen, Jack P.C. & Liu, Zhixue, 2012. "Factor Screening for Simulation with Multiple Responses : Sequential Bifurcation," Discussion Paper 2012-032, Tilburg University, Center for Economic Research.
  • Handle: RePEc:tiu:tiucen:631ee82e-aff7-468c-838a-966e800b6596
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    References listed on IDEAS

    as
    1. 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.
    2. Jack P. C. Kleijnen & Susan M. Sanchez & Thomas W. Lucas & Thomas M. Cioppa, 2005. "State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments," INFORMS Journal on Computing, INFORMS, vol. 17(3), pages 263-289, August.
    3. Haridy, Salah & Wu, Zhang & Lee, Ka Man & Bhuiyan, Nadia, 2013. "Optimal average sample number of the SPRT chart for monitoring fraction nonconforming," European Journal of Operational Research, Elsevier, vol. 229(2), pages 411-421.
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    6. 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.
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    8. Jack P.C. Kleijnen, 2015. "Design and Analysis of Simulation Experiments," International Series in Operations Research and Management Science, Springer, edition 2, number 978-3-319-18087-8, April.
    9. 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.
    10. 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.
    11. YalçInkaya, Özgür & Mirac Bayhan, G., 2009. "Modelling and optimization of average travel time for a metro line by simulation and response surface methodology," European Journal of Operational Research, Elsevier, vol. 196(1), pages 225-233, July.
    12. Christos Alexopoulos & David Goldsman & James R. Wilson (ed.), 2009. "Advancing the Frontiers of Simulation," International Series in Operations Research and Management Science, Springer, number 978-1-4419-0817-9, April.
    13. 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.
    14. Kleijnen, J.P.C. & Bettonvil, B.W.M., 1997. "Searching for important factors in simulation models with many factors : Sequential bifurcation," Other publications TiSEM be826993-22f9-4cb3-89df-3, Tilburg University, School of Economics and Management.
    15. Hua Shen & Hong Wan & Susan M. Sanchez, 2010. "A hybrid method for simulation factor screening," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(1), pages 45-57, February.
    16. 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.
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    Cited by:

    1. Ouyang, Linhan & Ma, Yizhong & Wang, Jianjun & Tu, Yiliu, 2017. "A new loss function for multi-response optimization with model parameter uncertainty and implementation errors," European Journal of Operational Research, Elsevier, vol. 258(2), pages 552-563.
    2. 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.
    3. 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.
    4. Mustafa Hekimoğlu & Yaman Barlas & Luis Luna-Reyes, 2016. "Sensitivity analysis for models with multiple behavior modes: a method based on behavior pattern measures," System Dynamics Review, System Dynamics Society, vol. 32(3-4), pages 332-362, July.
    5. Shi, Wen & Kleijnen, J.P.C., 2017. "Testing the Assumptions of Sequential Bifurcation for Factor Screening (revision of CentER DP 2015-034)," Discussion Paper 2017-006, Tilburg University, Center for Economic Research.
    6. 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.
    7. Kleijnen, Jack P.C., 2017. "Regression and Kriging metamodels with their experimental designs in simulation: A review," European Journal of Operational Research, Elsevier, vol. 256(1), pages 1-16.
    8. Shi, W. & Kleijnen, J.P.C., 2015. "Validating the Assumptions of Sequential Bifurcation in Factor Screening," Discussion Paper 2015-034, Tilburg University, Center for Economic Research.
    9. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    10. 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.

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    More about this item

    Keywords

    design of experiments; curse of dimensionality; sparse effects;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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