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Batch service systems with heterogeneous servers

dc.contributor.authorvan Ommeren J.-K.
dc.contributor.authorBaer N.
dc.contributor.authorMishra N.
dc.contributor.authorRoy D.
dc.date.accessioned2022-02-11T10:13:53Z
dc.date.available2022-02-11T10:13:53Z
dc.date.issued2020
dc.identifier.citationvan Ommeren, J. K., Baer, N., Mishra, N., & Roy, D. (2020). Batch service systems with heterogeneous servers. Queueing Systems, 95(3�. https://doi.org/10.1007/s11134-020-09654-y
dc.identifier.issn2570130
dc.identifier.urihttps://www.doi.org/10.1007/s11134-020-09654-y
dc.identifier.urihttp://hdl.handle.net/11718/25201
dc.description.abstractBulk-service multi-server queues with heterogeneous server capacity and thresholds are commonly seen in several situations such as passenger transport or package delivery services. In this paper, we develop a novel decomposition-based solution approach for such queues using arguments from renewal theory. We then obtain the distribution of the waiting time measure for multi-type server systems. We also obtain other useful performance measures such as utilization, expected throughput time, and expected queue lengths. � 2020, The Author(s).
dc.description.sponsorshipUniversity of Twente
dc.language.isoen_US
dc.publisherSpringer
dc.relation.ispartofQueueing Systems
dc.subjectDecomposition
dc.subjectHeterogeneous capacity
dc.subjectThreshold service
dc.titleBatch service systems with heterogeneous servers
dc.typeArticle
dc.rights.licenseCC BY
dc.contributor.affiliationStochastic Operations Research, University of Twente, Postbox 217, Enschede, 7500 AE, Netherlands
dc.contributor.affiliationCenter for Operations Research and Econometrics, UCLouvain, Louvain-la-Neuve, 1348, Belgium
dc.contributor.affiliationProduction and Quantitative Methods Area, Indian Institute of Management Ahmedabad, Ahmedabad, India
dc.contributor.institutionauthorvan Ommeren, J.-K., Stochastic Operations Research, University of Twente, Postbox 217, Enschede, 7500 AE, Netherlands
dc.contributor.institutionauthorBaer, N., Stochastic Operations Research, University of Twente, Postbox 217, Enschede, 7500 AE, Netherlands
dc.contributor.institutionauthorMishra, N., Center for Operations Research and Econometrics, UCLouvain, Louvain-la-Neuve, 1348, Belgium
dc.contributor.institutionauthorRoy, D., Production and Quantitative Methods Area, Indian Institute of Management Ahmedabad, Ahmedabad, India
dc.description.scopusid23398881500
dc.description.scopusid56245332300
dc.description.scopusid57193760358
dc.description.scopusid25522771400
dc.identifier.doi10.1007/s11134-020-09654-y
dc.identifier.endpage269
dc.identifier.startpage251
dc.identifier.issue03-Apr
dc.identifier.volume95


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