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Adaptive Scheduling of Non-Emergency Patient Transfers with Workload Balancing Constraints: A Mixed Integer Programming Approach

dc.contributor.authorFoster, Travis
dc.contributor.copyright-releaseNot Applicableen_US
dc.contributor.degreeMaster of Applied Scienceen_US
dc.contributor.departmentDepartment of Industrial Engineeringen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.external-examinerMajid Taghavien_US
dc.contributor.graduate-coordinatorAlireza Ghasemien_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.thesis-readerJ. Pemberton Cyrusen_US
dc.contributor.thesis-supervisorPeter VanBerkelen_US
dc.contributor.thesis-supervisorUday Venkatadrien_US
dc.date.accessioned2019-08-30T14:00:43Z
dc.date.available2019-08-30T14:00:43Z
dc.date.defence2019-08-27
dc.date.issued2019-08-30T14:00:43Z
dc.description.abstractEmergency Medical Services organizations are responsible for providing paramedic crews, vehicles and equipment to transfer patients from one location to another in emergency and non-emergency settings. In the non-emergency setting, they must solve difficult scheduling and assignment problems to ensure on-time arrival of patients and the efficient use of health care resources. The objective of this thesis is to develop a mathematical model that will assign Patient Transfer Units to non-emergency patient transfer requests and design a schedule that will minimize travel costs, balance workloads, and attempt to leave previously scheduled pickup times unchanged. This thesis also utilizes historical patient transfer data in the modelling process. The mathematical model provides decision support for the non-emergency patient transfer scheduling process.en_US
dc.identifier.urihttp://hdl.handle.net/10222/76366
dc.language.isoenen_US
dc.subjectOperations Researchen_US
dc.subjectVehicle Routingen_US
dc.subjectPatient Transfersen_US
dc.subjectAnalyticsen_US
dc.titleAdaptive Scheduling of Non-Emergency Patient Transfers with Workload Balancing Constraints: A Mixed Integer Programming Approachen_US

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