Service Operations Management

本研究将调查统计和数学模型，以告知一般排队系统和紧急医疗服务（EMS）系统的规划和管理。 我们将研究方法来预测EMS呼叫量在时间和空间，系统负载的方式影响医护人员在紧急情况下花费的时间，他们是否运送病人到医院，以及方法来平衡EMS负载在一个城市的急诊部门。 在更一般的水平上，我将制定和分析数学模型的排队等候，包括最近的实证研究结果表明，客户和服务器适应他们的行为，以应对负载的变化。 例如，服务器最初会随着负载的增加而加速，但如果负载长时间保持在高水平，则最终会由于疲劳而减速。 另一个例子是，服务器可能会在轮班结束时改变他们的行为。 我还将研究将经验发现转化为可用于支持规划的易于处理的数学模型的过程。 在学术层面上，该研究计划将有助于运筹学，运营管理在医疗保健和服务部门，EMS规划和管理领域。 它将解决基本问题的经验研究之间的相互作用，量化的平均服务时间取决于各种因素，和数学模型的服务率，制定的服务系统。 在实践层面上，本研究将有助于EMS系统和其他服务系统的改进规划方法的发展。 在加拿大和其他地方，特别是接受紧急护理的病人和一般接受服务的顾客，将从更有效和更高效地匹配供需的规划中受益。

This research will investigate statistical and mathematical models to inform planning and management of systems of waiting lines in general and emergency medical services (EMS) systems in particular. We will investigate methods to forecast EMS call volumes over time and space, the way in which system load impacts the time paramedics spend at the scene of an emergency and whether they transport the patient to a hospital, and methods to balance EMS load across the emergency departments in a city. At a more general level, I will formulate and analyse mathematical models of waiting lines that incorporate recent empirical findings indicating that customers and servers adapt their behaviour in response to changes in load. For example, servers initially speed up as load increases but eventually slow down due to fatigue if load remains high for an extended period. As another example, servers might change their behaviour towards the end of their shift. I will also study the process of translating empirical findings into tractable mathematical models that can be used to support planning. At an academic level, this research program will contribute to the fields of operations research, operations management in the healthcare and service sectors, and EMS planning and management. It will address fundamental issues regarding the interplay between empirical studies of queueing systems, which quantify how mean service times depend on various factors, and mathematical models of queueing systems, which are formulated in terms of service rates. At a practical level, this research will contribute to the development of improved planning methods for EMS systems and other service systems. Patients receiving emergency care in particular and customers receiving service in general, in Canada and elsewhere, will benefit from planning that matches supply and demand more effectively and efficiently.