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Stochastic regret minimization for revenue management problems with nonstationary demands

dc.contributor.authorZhang, Huanan
dc.contributor.authorShi, Cong
dc.contributor.authorQin, Chao
dc.contributor.authorHua, Cheng
dc.date.accessioned2017-01-06T20:51:16Z
dc.date.available2017-11-01T15:31:29Zen
dc.date.issued2016-09
dc.identifier.citationZhang, Huanan; Shi, Cong; Qin, Chao; Hua, Cheng (2016). "Stochastic regret minimization for revenue management problems with nonstationary demands." Naval Research Logistics (NRL) 63(6): 433-448.
dc.identifier.issn0894-069X
dc.identifier.issn1520-6750
dc.identifier.urihttps://hdl.handle.net/2027.42/135128
dc.description.abstractWe study an admission control model in revenue management with nonstationary and correlated demands over a finite discrete time horizon. The arrival probabilities are updated by current available information, that is, past customer arrivals and some other exogenous information. We develop a regret‐based framework, which measures the difference in revenue between a clairvoyant optimal policy that has access to all realizations of randomness a priori and a given feasible policy which does not have access to this future information. This regret minimization framework better spells out the trade‐offs of each accept/reject decision. We proceed using the lens of approximation algorithms to devise a conceptually simple regret‐parity policy. We show the proposed policy achieves 2‐approximation of the optimal policy in terms of total regret for a two‐class problem, and then extend our results to a multiclass problem with a fairness constraint. Our goal in this article is to make progress toward understanding the marriage between stochastic regret minimization and approximation algorithms in the realm of revenue management and dynamic resource allocation. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 433–448, 2016
dc.publisherWiley Periodicals, Inc.
dc.publisherSpringer
dc.subject.otherworst‐case bounds
dc.subject.otheralgorithms
dc.subject.otheradmission control
dc.subject.otherrevenue management
dc.subject.otherregret minimization
dc.subject.othernonhomogeneous Poisson processes
dc.titleStochastic regret minimization for revenue management problems with nonstationary demands
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelStatistics (Mathematical)
dc.subject.hlbtoplevelScience
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/135128/1/nav21704.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/135128/2/nav21704_am.pdf
dc.identifier.doi10.1002/nav.21704
dc.identifier.sourceNaval Research Logistics (NRL)
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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