We consider a real-time emergency medical service (EMS) vehicle patient transportation problem in which vehicles are assigned to patients so they can be transported to hospitals during an emergency. The objective is to minimize the total travel time of all vehicles while satisfying two types of time window constraints. The first requires each EMS vehicle to arrive at a patient’s location within a specified time window. The second requires the vehicle to arrive at the designated hospital within another time window. We allow an EMS vehicle to serve up to two patients instead of just one. The problem is shown to be NP-complete. We, therefore, develop a simulated annealing (SA) heuristic for efficient solution in real-time. A column generation algorithm is developed for determining a tight lower bound. Numerical results show that the proposed SA heuristic provides high-quality solutions in much less CPU time, when compared to the general-purpose solver. Therefore, it is suitable for implementation in a real-time decision support system, which is available via a web portal (www.rtdss.org).

我们考虑一个实时紧急医疗服务 (EMS) 车辆患者运输问题，其中车辆被分配给患者，以便他们可以在紧急情况下被运送到医院。目标是最小化所有车辆的总行程时间，同时满足两种类型的时间窗口约束。第一个要求每辆 EMS 车辆在指定的时间窗口内到达患者的位置。二是要求车辆在另一个时间窗口内到达定点医院。我们允许 EMS 车辆最多为两名患者提供服务，而不仅仅是一名患者。该问题被证明是 NP 完全的。因此，我们开发了一种模拟退火 (SA) 启发式算法，以实时有效地解决问题。开发了一种列生成算法来确定严格的下限。数值结果表明，与通用求解器相比，所提出的 SA 启发式可在更短的 CPU 时间内提供高质量的解决方案。因此，它适合在可通过门户网站 (www.rtdss.org) 获得的实时决策支持系统中实施。