| Health Sciences Centre (HSC) in Winnipeg is the major healthcare facility serving elective and emergency surgical patients in Manitoba, Northwestern Ontario, and Nunavut. An extensive evaluation of HSC's adult surgical patient flow revealed that one of the major barriers to smooth flow was the facility's Operating Room (OR) scheduling system. This thesis presents a new two-stage elective OR scheduling system for HSC, which generates weekly OR schedules that reduce artificial variability in order to facilitate smooth patient flow. The first stage reduces day-to-day variability by smoothing bed occupancy and patient volumes, increasing bed utilization, and evenly distributing OR time throughout the week. The second stage reduces the variability that may occur within a day by minimizing overtime, evenly distributing OR time among each operating theatre, and smoothing Post-Anaesthesia Care Unit (PACU) bed occupancy volumes and the number of cases that finish simultaneously. The scheduling processes in both stages are mathematically modelled as multi-objective optimization problems. An attempt was made to solve both models using lexicographic goal programming. However, this proved to be an unacceptable optimization method for the second stage, so a new multi-objective genetic algorithm, called Nondominated Sorting Genetic Algorithm II - Operating Room (NSGAII-OR), was developed. Results indicate that if the proposed system is implemented at HSC, the facility's surgical patient flow will likely improve. |
