Date of Award

12-18-2015

Publication Type

Master Thesis

Degree Name

M.A.Sc.

Department

Industrial and Manufacturing Systems Engineering

Keywords

goal programming, health service, scheduling, stochastic programming

Supervisor

Baki, M Fazle

Supervisor

Azab, Ahmed

Rights

info:eu-repo/semantics/openAccess

Abstract

Health care systems in Canada provide benefits to patients but have issues with costs and wait lists. Long wait lists negatively affect patients’ welfares. This in turn can increase costs because conditions can develop into more complicated ones over time. Operating rooms in a hospital are responsible for a significant portion of both costs and benefits; therefore, finding ways to use them more efficiently can reduce both the waste of tax dollars and the lengths of wait lists and can improve patients’ welfares. In this research, a stochastic weighted goal programming model is proposed to perform elective surgery scheduling under uncertainty of both surgical durations and patient lengths of stay. The model generates a Master Surgical Schedule that schedules surgical teams in operating room blocks in a way that minimizes four objectives, which are the deviations between the targeted number of surgeries and the actual number of surgeries performed, the deviations between the targeted number of hours for surgeries and the actual number of hours used for surgeries, the maximum expected number of patients in the recovery ward over the course of the planning horizon, and the difference between the maximum and minimum expected numbers of patients in the recovery ward over the course of the planning horizon. In addition, the impact of cancellations on the schedule is taken into account. A simulated annealing metaheuristic is developed to find near-optimal solutions. Discrete event simulation is used for validation and to demonstrate the system of operating rooms and recovery ward beds to relevant stakeholders in the health care sector.

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