EconPapers    
Economics at your fingertips  
 

Enhancing stochastic kriging for queueing simulation with stylized models

Haihui Shen, L. Jeff Hong and Xiaowei Zhang

IISE Transactions, 2018, vol. 50, issue 11, 943-958

Abstract: Stochastic kriging is a popular metamodeling technique to approximate computationally expensive simulation models. However, it typically treats the simulation model as a black box in practice and often fails to capture the highly nonlinear response surfaces that arise from queueing simulations. We propose a simple, effective approach to improve the performance of stochastic kriging by incorporating stylized queueing models that contain useful information about the shape of the response surface. We provide several statistical tools to measure the usefulness of the incorporated stylized models. We show that even a relatively crude stylized model can substantially improve the prediction accuracy of stochastic kriging.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1080/24725854.2018.1465242 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:50:y:2018:i:11:p:943-958

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20

DOI: 10.1080/24725854.2018.1465242

Access Statistics for this article

IISE Transactions is currently edited by Jianjun Shi

More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:uiiexx:v:50:y:2018:i:11:p:943-958