Maintaining fairness in stochastic chemotherapy scheduling

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buir.advisorKarsu, Özlem
buir.co-advisorGül, Serhat
dc.contributor.authorÇelik, Batuhan
dc.date.accessioned2024-07-08T13:45:19Z
dc.date.available2024-07-08T13:45:19Z
dc.date.copyright2024-06
dc.date.issued2024-06
dc.date.submitted2024-07-05
dc.descriptionCataloged from PDF version of article.
dc.descriptionThesis (Master's): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2024.
dc.descriptionIncludes bibliographical references (leaves 50-55).
dc.description.abstractChemotherapy scheduling is hard to manage under uncertainty in infusion durations, and focusing on expected performance measure values may lead to unfavorable outcomes for some patients. We aim to design daily patient appointment schedules considering fairness regarding patient waiting times. We propose using a metric that encourages fairness and efficiency in waiting time allocations. To optimize this metric, we formulate a two-stage stochastic mixed-integer nonlinear programming model. We employ a binary search algorithm to identify an optimal schedule, and then propose a modified binary search algorithm (MBSA) to enhance computational capability. Moreover, to address stochastic feasibility problems at each MBSA iteration, we introduce a novel reduce-and-augment algorithm that utilizes scenario set reduction and augmentation methods. We use real data from a major oncology hospital to show the efficacy of MBSA. We compare the schedules identified by MBSA with both the baseline schedules from the oncology hospital and those generated by commonly employed scheduling heuristics. We also compare our metric with a well-known inequity metric (the Gini coefficient) and a Rawlsian-type welfare function. Finally, we highlight the significance of considering uncertainty in infusion durations to maintain fairness while creating appointment schedules.
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2024-07-08T13:45:19Z No. of bitstreams: 1 B121749.pdf: 3042219 bytes, checksum: 36311265db0f89f5505772fdc24248f2 (MD5)en
dc.description.provenanceMade available in DSpace on 2024-07-08T13:45:19Z (GMT). No. of bitstreams: 1 B121749.pdf: 3042219 bytes, checksum: 36311265db0f89f5505772fdc24248f2 (MD5) Previous issue date: 2024-06en
dc.description.statementofresponsibilityby Batuhan Çelik
dc.embargo.release2025-01-03
dc.format.extentxi, 71 leaves : charts ; 30 cm.
dc.identifier.itemidB121749
dc.identifier.urihttps://hdl.handle.net/11693/115288
dc.language.isoEnglish
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectHealthcare operations
dc.subjectChemotherapy
dc.subjectScheduling
dc.subjectFairness
dc.subjectStochastic programming
dc.titleMaintaining fairness in stochastic chemotherapy scheduling
dc.title.alternativeRassal kemoterapi çizelgelemesinde adilliğin gözetilmesi
dc.typeThesis
thesis.degree.disciplineIndustrial Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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