Factor Screening for Simulation with Multiple Responses: Sequential Bifurcation
AbstractAbstract: Factor screening searches for the really important inputs (factors) among the many inputs that are changed in a realistic simulation experiment. Sequential bifurcation (or SB) is a sequential method that changes groups of inputs simultaneously. SB is the most e¢ cient and effective method if the following assumptions are satis ed: (i) second-order polynomials are adequate approximations of the input/output (I/O) functions implied by the simulation model; (ii) the signs of all first-order (or main) effects are known; (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 "batches" of inputs such that within a batch all inputs have the same sign for a specific type of output, so no cancellation of main effects occurs. MSB also applies Wald's sequential probability ratio test (SPRT) to obtain enough replicates for correctly classifying a group effect or an individual effect as important or unimportant. MSB enables e¢ cient selection of the initial number of replicates in SPRT. The paper also proposes a procedure to validate the three assumptions of MSB. The performance of MSB is examined through extensive Monte Carlo experiments that satisfy all MSB assumptions, and through a case study representing a logistic system in China; MSB performance is very promising.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2012-032.
Date of creation: 2012
Date of revision:
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Web page: http://center.uvt.nl
design of experiments; curse of dimensionality; sparse effects;
Other versions of this item:
- Shi, W. & Kleijnen, Jack P.C. & Liu, Zhixue, 2013. "Factor Sreening For Simulation With Multiple Responses: Sequential Bifurcation," Discussion Paper 2013-009, Tilburg University, Center for Economic Research.
- 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
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kleijnen, J.P.C. & Smits, M.T., 2003. "Performance metrics in supply chain management," Open Access publications from Tilburg University urn:nbn:nl:ui:12-111582, Tilburg University.
- 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.
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- Kleijnen, J.P.C. & Bettonvil, B.W.M., 1997.
"Searching for important factors in simulation models with many factors: Sequential bifurcation,"
Open Access publications from Tilburg University
urn:nbn:nl:ui:12-73905, Tilburg University.
- 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.
- Kleijnen, J.P.C., 2008. "Review of the book [Design and Analysis of Simulation Experiments]," Open Access publications from Tilburg University urn:nbn:nl:ui:12-4379049, Tilburg University.
- Kleijnen, J.P.C., 2003. "Supply Chain Simulation: A Survey," Discussion Paper 2003-103, Tilburg University, Center for Economic Research.
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