Controlled sequential factorial design for simulation factor screening
AbstractScreening 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 198 (2009)
Issue (Month): 2 (October)
Contact details of provider:
Web page: http://www.elsevier.com/locate/eor
Simulation Computer experiments Design of experiments Factor screening Sequential factorial design;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- 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.
- Shi, W. & Kleijnen, Jack P.C. & Liu, Zhixue, 2012.
"Factor Screening for Simulation with Multiple Responses: Sequential Bifurcation,"
2012-032, Tilburg University, Center for Economic Research.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.