Building cyclic master surgery schedules with leveled resulting bed occupancy
This paper proposes and evaluates a number of models for building surgery schedules with leveled resulting bed occupancy. The developed models involve two types of constraints. Demand constraints ensure that each surgeon (or surgical group) obtains a specific number of operating room blocks. Capacity constraints limit the available blocks on each day. Furthermore, the number of operated patients per block and the length of stay of each operated patient are dependent on the type of surgery. Both are considered stochastic, following a multinomial distribution. We develop a number of mixed integer programming based heuristics and a metaheuristic to minimize the expected total bed shortage and present computational results.
scheduling integer programming uncertainty modelling health services