Multi-period and multi-resource operating room scheduling under uncertainty: A case study

Efficient planning and scheduling is essential for timely treatment of patients and improving the quality of operating room services and activities. In the present study, attempts are made to investigate a multi-period and multi-resource operating room integrated planning and scheduling problem under uncertainty. To this end, a mixed integer linear programming model has been developed for minimizing the tardiness in surgeries, overtime and idle time. Constraints related to human resources, equipment, as well as beds in pre-operative holding unit, recovery unit, ward and intensive care unit are taken into consideration. The durations of surgeries and recoveries are assumed uncertain, and a robust optimization approach has been used to manage the uncertainty. Due to the complexity of the model and the inability to solve large-scale problems, a metaheuristic method based on the genetic algorithm and a constructive heuristic approach have been proposed. After setting the parameters of the solution approaches using the Taguchi method, numerical experiments are performed based on various instances, and the results obtained from solving the mathematical model are compared to the results of the proposed metaheuristic and heuristic approaches. The results indicate that the proposed methods have a very good performance and the heuristic approach outperforms the genetic approach because the objective function of the proposed constructive heuristic is on average, about 19% better than the objective function of the genetic approach. A case study is also conducted in a hospital. The results obtained from the comparison of the proposed approaches with the hospital scheduling show that overtime and idle time are significantly improved in the proposed approaches.