Multi-objective optimization for scheduling elective surgical patients at the Health Sciences Centre in Winnipeg

Abstract

Health Sciences Centre (HSC) in Winnipeg is the major healthcare facility serving Manitoba, Northwestern Ontario, and Nunavut. An evaluation of HSC’s adult surgical patient flow revealed that one major barrier to smooth flow was their 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 while the second stage reduces variability occurring within a day. 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 method for the second stage, so a new multi-objective genetic algorithm, Nondominated Sorting Genetic Algorithm II – Operating Room (NSGAII-OR), was developed. Results indicate that if the system is implemented at HSC, their surgical patient flow will likely improve.