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dc.contributor.authorYalçındağ, Semihen_US
dc.contributor.authorBaş Güre, Sedaen_US
dc.contributor.authorCarello, Giulianaen_US
dc.contributor.authorLanzarone, Ettoreen_US
dc.date.accessioned2020-07-17T06:15:04Z
dc.date.available2020-07-17T06:15:04Z
dc.date.issued2020-12
dc.identifier.citationYalçındağ, S., Baş Güre, S., Carello, G. & Lanzarone, E. (2020). A stochastic risk-averse framework for blood donation appointment scheduling under uncertain donor arrivals. Health Care Management Science, 23(4), 535-555. doi:10.1007/s10729-020-09508-2en_US
dc.identifier.issn1386-9620
dc.identifier.issn1572-9389
dc.identifier.urihttps://hdl.handle.net/11729/2349
dc.identifier.urihttp://dx.doi.org/10.1007/s10729-020-09508-2
dc.description.abstractBlood is a key resource in all health care systems, usually drawn from voluntary donors. We focus on the operations management in blood collection centers, which is a key step to guarantee an adequate blood supply and a good quality of service to donors, by addressing the so-called Blood Donation Appointment Scheduling problem. Its goal is to employ appointment scheduling to balance the production of blood units between days, in order to provide a reasonably constant supply to transfusion centers and hospitals, and reduce non-alignments between physicians' working times and donor arrivals at the collection center. We consider a two-phase solution framework taken from the literature, in which a deterministic linear programming model preallocates time slots to different blood types and a prioritization policy assigns the preallocated slots to the donors when they make a reservation. However, the problem is stochastic in nature and requires consideration of the uncertain arrivals of non-booked donors. In this work, to include the uncertain arrivals, we propose three stochastic counterparts of the preallocation model based on a risk-neutral objective and two risk-averse objectives, respectively, where the Conditional Value-at-Risk is considered as the risk measure in the last two methods. The resulting stochastic frameworks have been tested considering the historical data of one of the largest Italian collection centers, the Milan Department of the "Associazione Volontari Italiani Sangue" (AVIS). Results show the effectiveness of the stochastic models, especially the mean-risk one, and the need to include the uncertainty of arrivals in order to better balance the production of blood units.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.isversionof10.1007/s10729-020-09508-2
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBlood donation appointment schedulingen_US
dc.subjectProduction balancingen_US
dc.subjectUncertain donors' arrivalsen_US
dc.subjectRisk-neutral and risk-averse stochastic modelen_US
dc.subjectConditional value-at-risken_US
dc.subjectOperations researchen_US
dc.subjectOptimizationen_US
dc.subjectProgramming modelen_US
dc.subjectInventory managementen_US
dc.subjectSupply-and-demanden_US
dc.subjectValue-at-risken_US
dc.subjectChain network designen_US
dc.subjectAdulten_US
dc.subjectArticleen_US
dc.subjectBlood donoren_US
dc.subjectHematopoiesisen_US
dc.subjectHumanen_US
dc.subjectRisk assessmenten_US
dc.subjectStochastic modelen_US
dc.subjectSystem analysisen_US
dc.subjectUncertaintyen_US
dc.titleA stochastic risk-averse framework for blood donation appointment scheduling under uncertain donor arrivalsen_US
dc.typearticleen_US
dc.description.versionPublisher's Versionen_US
dc.relation.journalHealth Care Management Scienceen_US
dc.contributor.departmentIşık Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.contributor.departmentIşık University, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.contributor.authorID0000-0002-2603-5653
dc.identifier.volume23
dc.identifier.issue4
dc.identifier.startpage535
dc.identifier.endpage555
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorBaş Güre, Sedaen_US
dc.relation.indexWOSen_US
dc.relation.indexScopusen_US
dc.relation.indexPubMeden_US
dc.relation.indexSocial Sciences Citation Index (SSCI)en_US
dc.description.qualityQ2
dc.description.wosidWOS:000544832100001
dc.description.pubmedidPMID:32613350


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