An integrated approach for surgery scheduling under uncertainty

Operating rooms (ORs) account for high costs in hospitals. A well-designed surgery scheduling system can help improve facility utilization, thus reduce the cost. This paper is concerned with a surgery scheduling problem in the context where the number of surgeries in waiting list is beyond the capacity of OR. A surgeon may perform more than one surgery a day, and the surgeries of a surgeon are scheduled consecutively, which form a block. A model is proposed to determine which surgeries should be performed in the coming workday, as well as the corresponding start time of each block. We propose an integrated approach by combining two existing methods, i.e., sample average approximation (SAA) and robust linear programming. The new approach eliminates the number of variables in SAA model, hence can be solved more efficiently. Experiments show that the computation time of our approach is approximately one quarter of that of SAA. Cost sensitivity analysis is provided.