Operating room managers are facing increasingly complex challenges, namely in complying with waiting time targets before surgery. This paper proposes a framework that combines optimization and simulation to generate dynamic master surgery schedules for a long planning horizon, in which the schedules are optimized by an integer programming model and the demand levels are modelled using the simulation model. The developed approach allows the resulting operating room plan to balance waiting lists as it assigns more time to the specialties with higher demand in terms of time needed to perform all the surgeries in the corresponding waiting lists. The analysis of the results obtained for the proposed flexible rolling horizon approach were proven robust, and were compared to static and flexible long-term approaches, the former not allowing flexibility and the latter using a deterministic update of the demand. Considering throughput, tardiness and waiting time, the flexible rolling horizon approach showed the best results, while the static one had the worst results.

手术室经理面临着越来越复杂的挑战，即遵守手术前的等待时间目标。本文提出了一个结合优化和模拟的框架，以生成长期规划范围内的动态主手术计划，其中通过整数规划模型优化计划，并使用模拟模型对需求水平进行建模。所开发的方法允许最终的手术室计划平衡等待名单，因为它为在相应等待名单中执行所有手术所需的时间方面具有更高需求的专科分配更多时间。对提议的灵活滚动水平方法获得的结果的分析被证明是稳健的，并与静态和灵活的长期方法进行了比较，前者不允许灵活性，后者使用需求的确定性更新。考虑到吞吐量、延误和等待时间，灵活滚动水平方法显示出最好的结果，而静态方法的结果最差。