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Conference Paper: Simulation-based predictive analytics for dynamic queueing systems

TitleSimulation-based predictive analytics for dynamic queueing systems
Authors
Issue Date2017
PublisherIEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000674
Citation
Proceedings of 2017 Winter Simulation Conference (WSC), Las Vegas, NV, USA, 3-6 December 2017, p. 1716-1727 How to Cite?
AbstractSimulation and simulation optimization have primarily been used for static system design problems based on long-run average performance measures. Control or policy-based optimization has been a weakness, because it requires a way to predict future behavior based on current state and time information. This work is a first step in that direction with a focus on congestion measures for queueing systems. The idea is to fit predictive models to dynamic sample paths of the system state from a detailed simulation. We propose a two-step method to dynamically predict the probability that the system state belongs to a certain subset and test the performance of this method on two examples.
Persistent Identifierhttp://hdl.handle.net/10722/260901
ISSN
2023 SCImago Journal Rankings: 0.272

 

DC FieldValueLanguage
dc.contributor.authorOuyang, H-
dc.contributor.authorNelson, BL-
dc.date.accessioned2018-09-14T08:49:15Z-
dc.date.available2018-09-14T08:49:15Z-
dc.date.issued2017-
dc.identifier.citationProceedings of 2017 Winter Simulation Conference (WSC), Las Vegas, NV, USA, 3-6 December 2017, p. 1716-1727-
dc.identifier.issn0891-7736-
dc.identifier.urihttp://hdl.handle.net/10722/260901-
dc.description.abstractSimulation and simulation optimization have primarily been used for static system design problems based on long-run average performance measures. Control or policy-based optimization has been a weakness, because it requires a way to predict future behavior based on current state and time information. This work is a first step in that direction with a focus on congestion measures for queueing systems. The idea is to fit predictive models to dynamic sample paths of the system state from a detailed simulation. We propose a two-step method to dynamically predict the probability that the system state belongs to a certain subset and test the performance of this method on two examples.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000674-
dc.relation.ispartofWinter Simulation Conference (WSC) Proceedings-
dc.rightsWinter Simulation Conference (WSC) Proceedings. Copyright © IEEE.-
dc.titleSimulation-based predictive analytics for dynamic queueing systems-
dc.typeConference_Paper-
dc.identifier.emailOuyang, H: oyhy@hku.hk-
dc.identifier.authorityOuyang, H=rp02271-
dc.identifier.doi10.1109/WSC.2017.8247910-
dc.identifier.scopuseid_2-s2.0-85044533233-
dc.identifier.hkuros291645-
dc.identifier.spage1716-
dc.identifier.epage1727-
dc.publisher.placeUnited States-
dc.identifier.issnl0891-7736-

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