School of Economics and Management, Tongji University, Shanghai 200092, China.
J Healthc Eng. 2021 Nov 22;2021:1559050. doi: 10.1155/2021/1559050. eCollection 2021.
We formulated a new stochastic programming formulation to solve the dynamic scheduling problem in a given set of elective surgeries in the day of operation. The problem is complicated by the fact that the exact surgery durations are not known in advance. Elective surgeries could be performed in parallel in a subset of operating rooms. The appointment times and assignments of surgeries were planned by an experienced nurses in advance. We present a mathematical model to capture the nature of dynamic scheduling problem. We propose an efficient solution based on an improved genetic algorithm (IGA). Our numerical results showed that dynamic scheduling with the IGA improves the resource utilization as measured by surgeon waiting time and operation room idle time.
我们提出了一种新的随机规划公式来解决手术当天指定的选修手术中的动态调度问题。由于精确的手术持续时间事先无法得知，因此该问题较为复杂。选修手术可以在一组手术室的子集上并行进行。预约时间和手术分配由有经验的护士提前计划。我们提出了一个数学模型来捕捉动态调度问题的本质。我们提出了一种基于改进遗传算法（IGA）的有效解决方案。我们的数值结果表明，通过 IGA 的动态调度可以提高资源利用率，以测量外科医生等待时间和手术室空闲时间。
