Publication: Managing platelet supply through improved routing of blood collection vehicles
dc.contributor.author | Özener, Okan Örsan | |
dc.contributor.author | Ekici, Ali | |
dc.contributor.department | Industrial Engineering | |
dc.contributor.ozuauthor | ÖZENER, Okan Örsan | |
dc.contributor.ozuauthor | EKİCİ, Ali | |
dc.date.accessioned | 2018-10-08T11:14:14Z | |
dc.date.available | 2018-10-08T11:14:14Z | |
dc.date.issued | 2018-10 | |
dc.description.abstract | In this paper, we study the routing of blood collection vehicles for improving the platelet supply in the blood supply chain. In order to extract platelets, donated blood has to be processed at a central processing facility within six hours of donation time. Blood collection organizations have to dispatch collection vehicles and schedule pickups from the donation sites so that the donated units can be used in platelet production. Because of the accumulating behavior of donations and the six-hour processing time limit, routing of blood collection vehicles is a time-sensitive routing problem. We analyze the routing decisions in such a setting and propose an integrated clustering and routing framework to collect and process the maximum number of donations for platelet production. In our analysis, motivated by the practices in real-life, we cluster the donation sites so that only a single vehicle serves the donation sites in each cluster. In the proposed framework, we make the clustering and routing decisions in an integrated manner so that we can foresee the impact of adding a donation site to a cluster on the routing decisions. For the routing step, we propose several heuristic algorithms, two of which have a greedy nature and the others are based on a priori tour generation and selection scheme. To evaluate the performances of the proposed heuristics, we develop an upper bound by relaxing the number of vehicles so that one vehicle is available for each donation site. Using the proposed heuristic algorithms, we obtain solutions with around 15% optimality gaps with respect to the upper bound. | en_US |
dc.description.sponsorship | TÜBİTAK | |
dc.identifier.doi | 10.1016/j.cor.2018.05.011 | en_US |
dc.identifier.endpage | 126 | en_US |
dc.identifier.issn | 0305-0548 | en_US |
dc.identifier.scopus | 2-s2.0-85047606340 | |
dc.identifier.startpage | 113 | en_US |
dc.identifier.uri | http://hdl.handle.net/10679/5996 | |
dc.identifier.uri | https://doi.org/10.1016/j.cor.2018.05.011 | |
dc.identifier.volume | 98 | en_US |
dc.identifier.wos | 000440526800009 | |
dc.language.iso | eng | en_US |
dc.peerreviewed | yes | en_US |
dc.publicationstatus | Published | en_US |
dc.publisher | Elsevier | en_US |
dc.relation | info:eu-repo/grantAgreement/TUBITAK/1001 - Araştırma/112M945 | |
dc.relation.ispartof | Computers and Operations Research | |
dc.relation.publicationcategory | International Refereed Journal | |
dc.rights | restrictedAccess | |
dc.subject.keywords | Blood supply chain | en_US |
dc.subject.keywords | Platelet production | en_US |
dc.subject.keywords | Processing time limit | en_US |
dc.subject.keywords | Vehicle routing | en_US |
dc.title | Managing platelet supply through improved routing of blood collection vehicles | en_US |
dc.type | article | en_US |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | 5dd73c02-fd2d-43e0-9a23-71bab9ae0b6b | |
relation.isOrgUnitOfPublication.latestForDiscovery | 5dd73c02-fd2d-43e0-9a23-71bab9ae0b6b |
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