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- Publisher Website: 10.1109/WSC.2016.7822122
- Scopus: eid_2-s2.0-85014150625
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Conference Paper: Simulation metamodeling in the presence of model inadequacy
Title | Simulation metamodeling in the presence of model inadequacy |
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Authors | |
Issue Date | 2017 |
Publisher | IEEE. |
Citation | 2016 Winter Simulation Conference (WSC 2016), Washington, DC, 11-14 December 2016. In Proceedings - Winter Simulation Conference, 2017, p. 566-577 How to Cite? |
Abstract | © 2016 IEEE. A simulation model is often used as a proxy for the real system of interest in a decision-making process. However, no simulation model is totally representative of the reality. The impact of the model inadequacy on the prediction of system performance should be carefully assessed. We propose a new metamodeling approach to simultaneously characterize both the simulation model and its model inadequacy. Our approach utilizes both simulation outputs and real data to predict system performance, and accounts for four types of uncertainty that arise from the unknown performance measure of the simulation model, simulation errors, unknown model inadequacy, and observation errors of the real system, respectively. Numerical results show that the new approach provides more accurate predictions in general. |
Persistent Identifier | http://hdl.handle.net/10722/271488 |
ISSN | 2023 SCImago Journal Rankings: 0.272 |
DC Field | Value | Language |
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dc.contributor.author | Zhang, Xiaowei | - |
dc.contributor.author | Zou, Lu | - |
dc.date.accessioned | 2019-07-02T07:16:12Z | - |
dc.date.available | 2019-07-02T07:16:12Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | 2016 Winter Simulation Conference (WSC 2016), Washington, DC, 11-14 December 2016. In Proceedings - Winter Simulation Conference, 2017, p. 566-577 | - |
dc.identifier.issn | 0891-7736 | - |
dc.identifier.uri | http://hdl.handle.net/10722/271488 | - |
dc.description.abstract | © 2016 IEEE. A simulation model is often used as a proxy for the real system of interest in a decision-making process. However, no simulation model is totally representative of the reality. The impact of the model inadequacy on the prediction of system performance should be carefully assessed. We propose a new metamodeling approach to simultaneously characterize both the simulation model and its model inadequacy. Our approach utilizes both simulation outputs and real data to predict system performance, and accounts for four types of uncertainty that arise from the unknown performance measure of the simulation model, simulation errors, unknown model inadequacy, and observation errors of the real system, respectively. Numerical results show that the new approach provides more accurate predictions in general. | - |
dc.language | eng | - |
dc.publisher | IEEE. | - |
dc.relation.ispartof | Proceedings - Winter Simulation Conference | - |
dc.title | Simulation metamodeling in the presence of model inadequacy | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/WSC.2016.7822122 | - |
dc.identifier.scopus | eid_2-s2.0-85014150625 | - |
dc.identifier.spage | 566 | - |
dc.identifier.epage | 577 | - |
dc.identifier.issnl | 0891-7736 | - |