Abstract This paper addresses the multi-period ambulance redeployment planning problem in a two-tiered Emergency Medical System (EMS) where two types of ambulances are used to respond to two categories of emergency calls. In order to account for the uncertainty inherent to both categories of demand, we propose a two-stage stochastic programming model that aims at finding a cost-effective ambulance redeployment. The model tries to minimize the total cost, which encompasses ambulance relocation cost, the dispatching cost, and the penalty cost incurred by the unsatisfied demand, over a multi-period planning horizon. In order to overcome the computational complexity of the proposed model, two heuristics are proposed: a Temporal Decomposition Heuristic (HDT), and a Lagrangian Relaxation based Heuristic (SBG). A simulation model is then proposed to evaluate the service level of the EMS system and ambulance utilization while accounting for more realistic features of the problem. The computational experiments are carried out using real-world data provided by the EMS system of the northern region of Tunisia. The results show the excellent performance of HDT as it provides a near-optimal solution within a reasonable computational time. The simulation also demonstrates that the service level of the EMS system is higher if HDT is used.

中文翻译：

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二级急诊医疗服务系统的多周期随机规划模型

摘要 本文解决了两级紧急医疗系统 (EMS) 中的多阶段救护车重新部署计划问题，其中使用两种类型的救护车来响应两类紧急呼叫。为了解决这两类需求固有的不确定性，我们提出了一个两阶段随机规划模型，旨在找到具有成本效益的救护车重新部署。该模型试图在多周期规划范围内最小化总成本，包括救护车搬迁成本、调度成本和因需求未得到满足而产生的惩罚成本。为了克服所提出模型的计算复杂性，提出了两种启发式：时间分解启发式（HDT）和基于拉格朗日松弛的启发式（SBG）。然后提出了一个模拟模型来评估 EMS 系统的服务水平和救护车的利用率，同时考虑到问题的更现实特征。计算实验是使用突尼斯北部地区 EMS 系统提供的真实世界数据进行的。结果表明 HDT 的出色性能，因为它在合理的计算时间内提供了近乎最优的解决方案。模拟还表明，如果使用 HDT，EMS 系统的服务水平会更高。结果表明 HDT 的出色性能，因为它在合理的计算时间内提供了近乎最优的解决方案。模拟还表明，如果使用 HDT，EMS 系统的服务水平会更高。结果表明 HDT 的出色性能，因为它在合理的计算时间内提供了近乎最优的解决方案。模拟还表明，如果使用 HDT，EMS 系统的服务水平会更高。