Surgery scheduling with recovery resources
针对单日择期手术排程问题，考虑外科医生、手术室和麻醉后恢复单元，提出混合整数规划模型和两阶段启发式算法，在确定性和随机环境下均表现优异，易于实施。
Surgical services are large revenue sources that account for a large portion of hospital expenses. Thus, efficient resource allocation is crucial in this system; however, this is a challenging problem, in part due to the interaction of the different stages of the surgery delivery system and the uncertainty of surgery and recovery durations. This article focuses on single-day in-patient elective surgery scheduling considering surgeons, operating rooms (ORs), and the post-anesthesia care unit (recovery). We propose a mixed-integer programming formulation of this problem and then present a fast two-phase heuristic: phase 1 is used for determining the number of ORs to open for the day and surgeon-to-OR assignments, and phase 2 is used for surgical case sequencing. Both phases have provable worst-case performance guarantees and excellent average case performance. We evaluate schedules under uncertainty using a discrete-event simulation model based on data provided by a mid-sized hospital. We show that the fast and easy-to-implement two-phase heuristic performs extremely well, in both deterministic and stochastic settings. The new methods developed reduce the computational barriers to implementation and demonstrate that hospitals can realize substantial benefits without resorting to sophisticated optimization software implementations.