Simulation Optimization Of Operating Room Schedules For Elective Orthopaedic Surgeries

The aim of this thesis was to solve the problem of scheduling elective surgeries in a multiple operating room setting with the goal of minimizing the amount of overtime incurred. While surgical durations cannot always be perfectly estimated and vary by procedure and surgeon, we propose an approach that relies on leveraging the stochastic nature of surgical durations to simulate each operating day and understand the probability of incurring overtime under a certain schedule of surgeries. Through experimentation with three optimization techniques that strategically re-schedule surgeries, two showed promising results being able to reduce the total number of overtime surgeries by 12-15%, equivalent to approximately 1h of total monthly overtime. This approach serves as a tool for improving schedules and supporting decision makers at any hospital dealing with elective surgeries. Our contribution involves introducing the simulation optimization model and describing the data-driven approach to analyzing the scheduling problem.