Minimax Regret Optimization with Applications in Healthcare Operations
department or school: Applied Science, Faculty of
department or school: Engineering, School of (Okanagan)
data provider: DSpace
degree campus: UBCO
creator: Pourrezaiekhaligh, Pooya
issued: 2023-07-20T17:12:12Z
issued: 2023
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: Uncertainty is an inherent characteristic of healthcare due to the complexity and variability of the healthcare system. The healthcare industry constantly evolves, and new medical technologies and treatments are being developed, leading to new challenges and opportunities. Managing uncertainty is critical for healthcare providers as it can impact the quality of care provided to patients and the financial performance of healthcare organizations. Therefore, developing effective strategies for managing uncertainty is essential for achieving better patient outcomes and optimizing resource allocation in healthcare. This thesis explores the application of the regret minimization model to deal with demand uncertainty in a home health care location problem and uncertainty of surgery duration in an operating room planning problem. The objective is to find a balance between being conservative and being computationally efficient in decision-making under uncertainty. The literature review highlights the limitations of robust optimization models, which tend to be overly conservative and ignore the potential benefits of more optimistic scenarios. In contrast, regret minimization models provide a framework that accounts for potential regret in decision-making, leading to less conservative solutions. In the home health care planning problem, the regret minimization model is applied to determine the optimal location of home health care facilities, considering demand uncertainty. The results show that the regret minimization model yields solutions that are less conservative than those obtained using the robust optimization model. In the operating room planning problem, the regret minimization model is applied to optimize the allocation of surgeries to operating rooms, considering the uncertainty of surgery duration. The results show that the regret minimization model outperforms the robust optimization model regarding conservatism. Overall, this thesis demonstrates the effectiveness …
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/85281
note: Minimax Regret Optimization withApplications in Healthcare OperationsbyPooya PourrezaiekhalighB.Sc., The Babol Noshirvani University of Technology, 2016M.Sc., The University of Tehran, 2019A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF APPLIED SCIENCEinTHE COLLEGE OF GRADUATE STUDIES(Mechanical Engineering)THE UNIVERSITY OF BRITISH COLUMBIA(Okanagan)July 2023© Pooya Pourrezaiekhaligh, 2023The following individuals certify that they have read, and recommendto the College of Graduate Studies for acceptance, a thesis entitled:Minimax Regret Optimization with Applications in Health-care Operationssubmitted by Pooya Pourrezaiekhaligh in partial fulfilment of the re-quirements of the degree of Master of Applied ScienceDr. Babak Mohamadpour Tosarkani, School of EngineeringSupervisorDr. Amir Ardestani-Jaafari, Faculty of ManagementCo-supervisorDr. Qian Chen, School of EngineeringSupervisory Committee MemberDr. Eric Li, Faculty of ManagementSupervisory Committee MemberDr. Sumi Siddiqua, School of EngineeringUniversity ExamineriiAbstractUncertainty is an inherent characteristic of healthcare due to the com-plexity and variability of the healthcare system. The healthcare industryconstantly evolves, and new medical technologies and treatments are beingdeveloped, leading to new challenges and opportunities. Managing uncer-tainty is critical for healthcare providers as it can impact the quality of careprovided to patients and the financial performance of healthcare organiza-tions. Therefore, developing effective strategies for managing uncertaintyis essential for achieving better patient outcomes and optimizing resourceallocation in healthcare.This thesis explores the application of the regret minimization modelto deal with demand uncertainty in a home health care location problemand uncertainty of surgery duration in an operating room planning prob-lem. The objective is to find a balance between being conservative andbeing computationally…
has type: Thesis/Dissertation
date issued: 2023-09
is shown at: 10.14288/1.0434256
language: eng
degree discipline: Mechanical Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Tosarkani, Babak Mohamadpour
contributor: Ardestani-Jaafari, Amir
type: Text
identifier URI: http://hdl.handle.net/2429/85281