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Optimal Pricing and Admission Control in a Queueing System with Periodically Varying Parameters

dc.contributor.authorYoon, Seunghwanen_US
dc.contributor.authorLewis, Mark E.en_US
dc.date.accessioned2006-09-11T19:12:40Z
dc.date.available2006-09-11T19:12:40Z
dc.date.issued2004-07en_US
dc.identifier.citationYoon, Seunghwan; Lewis, Mark E.; (2004). "Optimal Pricing and Admission Control in a Queueing System with Periodically Varying Parameters." Queueing Systems 47(3): 177-199. <http://hdl.handle.net/2027.42/47630>en_US
dc.identifier.issn0257-0130en_US
dc.identifier.issn1572-9443en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/47630
dc.description.abstractWe consider congestion control in a nonstationary queueing system. Assuming that the arrival and service rates are bounded, periodic functions of time, a Markov decision process (MDP) formulation is developed. We show under the infinite horizon discounted and average reward optimality criteria, for each fixed time, optimal pricing and admission control strategies are nondecreasing in the number of customers in the system. This extends stationary results to the nonstationary setting. Despite this result, the problem still seems intractable. We propose an easily implementable pointwise stationary approximation (PSA) to approximate the optimal policies, suggest a heuristic to improve the implementation of the PSA and verify its usefulness via a numerical study.en_US
dc.format.extent251576 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science+Business Mediaen_US
dc.subject.otherEconomics / Management Scienceen_US
dc.subject.otherComputer Communication Networksen_US
dc.subject.otherSystems Theory, Controlen_US
dc.subject.otherProbability Theory and Stochastic Processesen_US
dc.subject.otherOperation Research/Decision Theoryen_US
dc.subject.otherProduction/Logisticsen_US
dc.titleOptimal Pricing and Admission Control in a Queueing System with Periodically Varying Parametersen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelManagementen_US
dc.subject.hlbsecondlevelIndustrial and Operations Engineeringen_US
dc.subject.hlbsecondlevelEconomicsen_US
dc.subject.hlbtoplevelBusinessen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Industrial and Operations Engineering, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI, 48109-2117, USAen_US
dc.contributor.affiliationumDepartment of Industrial and Operations Engineering, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI, 48109-2117, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/47630/1/11134_2004_Article_5273757.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1023/B:QUES.0000035313.20223.3fen_US
dc.identifier.sourceQueueing Systemsen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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