Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming

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dc.contributor.authorVisentin, Andrea
dc.contributor.authorPrestwich, Steven D.
dc.contributor.authorRossi, Roberto
dc.contributor.authorTarim, S. Armagan
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderEuropean Regional Development Funden
dc.date.accessioned2021-02-19T13:35:07Z
dc.date.available2021-02-19T13:35:07Z
dc.date.issued2021-01-13
dc.date.updated2021-02-19T13:24:09Z
dc.description.abstractA well-known control policy in stochastic inventory control is the policy, in which inventory is raised to an order-up-to-level S at a review instant R whenever it falls below reorder-level s. To date, little or no work has been devoted to developing approaches for computing policy parameters. In this work, we introduce a hybrid approach that exploits tree search to compute optimal replenishment cycles, and stochastic dynamic programming to compute levels for a given cycle. Up to 99.8% of the search tree is pruned by a branch-and-bound technique with bounds generated by dynamic programming. A numerical study shows that the method can solve instances of realistic size in a reasonable time.en
dc.description.sponsorshipScience Foundation Ireland (under Grant number 12/RC/2289-P2, which is co-funded under the European Regional Development Fund)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationVisentin, A., Prestwich, S., Rossi, R. and Tarim, S. A. (2021) 'Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming', European Journal of Operational Research, doi: 10.1016/j.ejor.2021.01.012en
dc.identifier.doi10.1016/j.ejor.2021.01.012en
dc.identifier.endpage9en
dc.identifier.issn0377-2217
dc.identifier.journaltitleEuropean Journal of Operational Researchen
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/11078
dc.language.isoenen
dc.publisherElsevieren
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S037722172100014X
dc.rights© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectInventoryen
dc.subject(R,s,S) policyen
dc.subjectDemand uncertaintyen
dc.subjectStochastic lot sizingen
dc.titleComputing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programmingen
dc.typeArticle (peer-reviewed)en
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