Publication:
Optimal control of production-inventory systems with correlated demand inter-arrival and processing times

dc.contributor.departmentDepartment of Business Administration
dc.contributor.departmentN/A
dc.contributor.kuauthorTan, Barış
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Business Administration
dc.contributor.schoolcollegeinstituteGraduate School of Business
dc.contributor.schoolcollegeinstituteCollege of Administrative Sciences and Economics
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid28600
dc.date.accessioned2024-11-09T13:26:03Z
dc.date.issued2020
dc.description.abstractWe consider the production control problem of a production-inventory system with correlated demand inter-arrival and processing times that are modeled as Markovian Arrival Processes. The control problem is minimizing the expected average cost of the system in the steady-state by controlling when to produce an available part. We prove that the optimal control policy is the state-dependent threshold policy. We evaluate the performance of the system controlled by the state-dependent threshold policy by using the Matrix Geometric method. We determine the optimal threshold levels of the system by using policy iteration. We then investigate how the autocorrelation of the arrival and service processes impact the performance of the system. Finally, we compare the performance of the optimal policy with 3 benchmark policies: a state-dependent policy that uses the distribution of the inter-event times but assumes i.i.d.inter-event times, a single-threshold policy that uses both the distribution and also the autocorrelation, and a single-threshold policy that uses the distribution of the inter-event times but assumes they are not correlated. Our analysis demonstrates that ignoring autocorrelation in setting the parameters of the production policy causes significant errors in the expected inventory and backlog costs. A single-threshold policy that sets the threshold based on the distribution and also the autocorrelation performs satisfactorily for systems with negative autocorrelation. However, ignoring positive correlation yields high errors for the total cost. Our study shows that an effective production control policy must take correlations in service and demand processes into account.
dc.description.fulltextYES
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuTÜBİTAK
dc.description.sponsoredbyTubitakEuEU
dc.description.sponsorshipEuropean Union ECSEL Joint Undertaking, Productive 4.0
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TÜBİTAK)
dc.description.versionPublisher version
dc.description.volume228
dc.formatpdf
dc.identifier.doi10.1016/j.ijpe.2020.107692
dc.identifier.embargoNO
dc.identifier.filenameinventorynoIR02144
dc.identifier.issn0925-5273
dc.identifier.linkhttps://doi.org/10.1016/j.ijpe.2020.107692
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85080119865
dc.identifier.urihttps://hdl.handle.net/20.500.14288/3470
dc.keywordsCorrelated demand arrival
dc.keywordsCorrelated service process
dc.keywordsMarkovian arrival processes
dc.keywordsProduction systems
dc.keywordsState-dependent threshold policies
dc.languageEnglish
dc.publisherElsevier
dc.relation.grantno737459
dc.relation.grantno217M145
dc.relation.urihttp://cdm21054.contentdm.oclc.org/cdm/ref/collection/IR/id/8763
dc.sourceInternational Journal of Production Economics
dc.subjectServers
dc.subjectPublic policy
dc.subjectStationary distribution
dc.titleOptimal control of production-inventory systems with correlated demand inter-arrival and processing times
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authoridN/A
local.contributor.authorid0000-0002-2584-1020
local.contributor.kuauthorDizbin, Nima Manafzadeha
local.contributor.kuauthorTan, Barış
relation.isOrgUnitOfPublicationca286af4-45fd-463c-a264-5b47d5caf520
relation.isOrgUnitOfPublication.latestForDiscoveryca286af4-45fd-463c-a264-5b47d5caf520

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