From offline to online kidney exchange optimization

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dc.contributor.authorChisca, Danuta Sorina
dc.contributor.authorLombardi, Michele
dc.contributor.authorMilano, Michela
dc.contributor.authorO'Sullivan, Barry
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2019-02-18T19:13:40Z
dc.date.available2019-02-18T19:13:40Z
dc.date.issued2018-12-17
dc.date.updated2019-02-18T18:29:14Z
dc.description.abstractKidney exchange programs enable willing, but incompatible, donor-patient pairs to swap donors, thus allowing persons suffering from organ failure to access transplantation. Choosing which pairs to match requires solving a stochastic online optimization problem where patients and donors arrive over time. Despite this, most of the related scientific literature has focused on deterministic offline models. In this paper, we present a simple approach to employ a model for the offline Kidney Exchange Problem (KEP) as the basis of an on-line anticipatory algorithm. Our approach grounds on existing techniques for the on-line KEP, but it generalizes them and provides a more accurate estimate of the expected impact of current decisions. In an experimentation based on a state-of-the-art donor pool generation method, the approach provides improvements in terms of quality and is able to deal with realistic instance size in reasonable time.en
dc.description.statusNot peer revieweden
dc.description.urihttp://ictai2018.org/en
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationChisca, D. S., Lombardi, M., Milano, M. and O'Sullivan, B. (2018) 'From offline to online kidney exchange optimization', 30th International Conference on Tools with Artificial Intelligence (ICTAI), Volos, Greece, 5-7 November. doi:10.1109/ICTAI.2018.00095en
dc.identifier.doi10.1109/ICTAI.2018.00095
dc.identifier.endpage591en
dc.identifier.isbn978-1-5386-7449-9
dc.identifier.issn1082-3409
dc.identifier.issn2375-0197
dc.identifier.issn978-1-5386-7450-5
dc.identifier.startpage587en
dc.identifier.urihttps://hdl.handle.net/10468/7515
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartof2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)
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://ieeexplore.ieee.org/abstract/document/8576093
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.,en
dc.subjectDecision makingen
dc.subjectKidneyen
dc.subjectOptimisationen
dc.subjectPatient diagnosisen
dc.subjectStochastic processesen
dc.subjectSurgeryen
dc.subjectKidney exchange programsen
dc.subjectDonor-patient pairsen
dc.subjectOrgan failureen
dc.subjectStochastic online optimization problemen
dc.subjectOn-line anticipatory algorithmen
dc.subjectTransplantationen
dc.subjectOnline kidney exchange optimizationen
dc.subjectOffline kidney exchange problemen
dc.subjectDonor pool generationen
dc.subjectOptimizationen
dc.subjectScalabilityen
dc.subjectMathematical modelen
dc.subjectApproximation algorithmsen
dc.subjectConferencesen
dc.subjectAnticipatory algorithmen
dc.subjectOnline stochastic kidney exchangeen
dc.titleFrom offline to online kidney exchange optimizationen
dc.typeConference itemen
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