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Characteristics of optimal workload allocation for closed queueing networks

dc.contributor.authorLee, Heungsoon Felixen_US
dc.contributor.authorSrinivasan, Mandyam M.en_US
dc.contributor.authorYano, Candace Araien_US
dc.date.accessioned2006-04-10T14:40:11Z
dc.date.available2006-04-10T14:40:11Z
dc.date.issued1991-07en_US
dc.identifier.citationLee, Heungsoon Felix, Srinivasan, Mandyam M., Yano, Candace A. (1991/07)."Characteristics of optimal workload allocation for closed queueing networks." Performance Evaluation 12(4): 255-268. <http://hdl.handle.net/2027.42/29251>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V13-48TDCRJ-24/2/37de9f348badbf0edbd1303ea32b0035en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/29251
dc.description.abstractWe consider the problem of allocating a given workload among the stations in a multi-server product-form closed queueing network to maximize the throughput. We first investigate properties of the throughput function and prove that it is pseudoconcave for some special cases. Some other characteristics of the optimal workload and its physical interpretation are also provided. We then develop two computational procedures to find the optimum workload allocation under the assumption that the throughput function is pseudoconcave in general. The primary advantage of assuming pseudoconcavity is that, under this assumption, satisfaction of first order necessary conditions is sufficient for optimality. Computational experience with these algorithms provides additional support for the validity of this assumption. Finally, we generalize the solution procedure to accommodate bounds on the workloads at each station.en_US
dc.format.extent1006425 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleCharacteristics of optimal workload allocation for closed queueing networksen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelComputer Scienceen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Industrial & Operations Engineering, University of Michigan, Ann Arbor, MI 48109-2117, USAen_US
dc.contributor.affiliationumDepartment of Industrial & Operations Engineering, University of Michigan, Ann Arbor, MI 48109-2117, USAen_US
dc.contributor.affiliationotherDepartment of Industrial Engineering, Southern Illinois University, Edwardsville, IL 62026-1802, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/29251/1/0000308.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0166-5316(91)90004-Men_US
dc.identifier.sourcePerformance Evaluationen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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