Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98343
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorXie, Jen_US
dc.creatorZhu, Ten_US
dc.creatorChao, AKen_US
dc.creatorWang, Sen_US
dc.date.accessioned2023-04-27T01:04:56Z-
dc.date.available2023-04-27T01:04:56Z-
dc.identifier.issn0254-5330en_US
dc.identifier.urihttp://hdl.handle.net/10397/98343-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© Springer Science+Business Media New York 2016en_US
dc.rightsThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10479-016-2370-6.en_US
dc.subjectFinite truncationen_US
dc.subjectPerformance analysisen_US
dc.subjectPriority upgradeen_US
dc.titlePerformance analysis of service systems with priority upgradesen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationTitle on author’s file: Performance Analysis of Service Systems with Upgrade of Prioritiesen_US
dc.identifier.spage683en_US
dc.identifier.epage705en_US
dc.identifier.volume253en_US
dc.identifier.issue1en_US
dc.identifier.doi10.1007/s10479-016-2370-6en_US
dcterms.abstractIn this paper, we study the performance of service systems with priority upgrades. We model the service system as a single-server two-class priority queue, with queue 1 as the normal queue and queue 2 as the priority queue. The queueing model of interest has various applications in healthcare services, perishable inventory and project management. We comprehensively examine the system’s stationary distribution, computational algorithm design and sensitivity analysis. We observe that when queue 2 is large, the conditional distribution of queue 1 approximates a Poisson distribution. The tail probability of queue 2 decays geometrically, while the tail probability of queue 1 decays much faster than queue 2’s. This helps us design an algorithm that computed the stationary distribution. Finally, by using the algorithm, we perform a sensitivity analysis on various system parameters, i.e., the arrival rates, service rates and the upgrade rate. The numerical study provides helpful insights into designing such service systems.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAnnals of operations research, June 2017, v. 253, no. 1, p. 683-705en_US
dcterms.isPartOfAnnals of operations researchen_US
dcterms.issued2017-06-
dc.identifier.scopus2-s2.0-84997017986-
dc.identifier.eissn1572-9338en_US
dc.description.validate202304 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberLMS-0403-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6698628-
dc.description.oaCategoryGreen (AAM)en_US
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