Master Surgical Scheduling of Multi-Surgeon Surgical Schedules Using a Mixed-Integer Linear Programming Model and Genetic Algorithms

The purpose of this work is to develop a master surgical scheduling for a case study of a large-scale public hospital in Thailand using a mixed-integer linear programming model (MILP) and a genetic algorithm (GA). Due to the high volume of operations that must be handled every day, our main objective is to create a schedule that maximizes OR utilization, minimizes room overtime, and reduces idle time between surgical patients. The data from Thammasat University Hospital were analyzed and simulated to generate a timetable from daily to weekly schedule. Our results show that an exact solution can be obtained by MILP for a simple problem while a large CPU run time is incurred for the complex problems. GA provided the optimal solution for a complex large-scale problem. The schedule generated by the proposed GA is more flexible and the staff can improve it to obtain more practical timetable in real-life situations, such as increasing the number of surgeries, setting a time block for specific surgical specialties, and handling emergency cases.