Stochastic scheduling and capacity planning models and methods for operations and service management, with an application to healthcare industry

该提案的目标是开发一个系统范围的数学框架，用于在运营和服务管理的不确定性下改进调度和容量规划决策，并将其应用于医疗保健行业，以实现更好的患者服务（更少的等待时间和/或实现等待时间目标）和更低的服务提供商成本（更少的加班和/或更少的容量要求）。医疗保健的挑战在世界上越来越多，及时获得医疗保健在加拿大尤其令人担忧。改进的一种方法是有效的调度和容量规划。当系统中存在不确定性时，这变得更加重要和具有挑战性。不确定性涉及患者（类型、数量）、资源（床位可用性、手术持续时间）和手术（在医院/康复单位的住院时间）。我考虑一个系统，其中工作（患者）在每个周期到达并排队等待，直到它们在处理器中被处理（例如，手术室（OR））然后保存在有限容量的存储区域（例如，在他们离开系统之前的一段时间。工件的到达过程、加工持续时间和在存储区花费的时间都存在不确定性。（相同或类似类型系统的子集适用于操作和服务管理中的其他设置。）这种系统的有效调度和容量规划要求采取全系统的办法。然而，数学上的挑战迫使研究人员（包括我自己）在这个系统中孤立地研究较小的问题。我将建立在我以前的研究预约和或块调度系统考虑开发一个系统范围内的数学框架。我将使用动态规划，非光滑凸优化方法，基于离散凸性的算法，模拟和过程映射。这项研究的潜在好处是减少病人的等待时间，改善不确定性下的容量规划，并结合调度和容量规划方法的进步。我也渴望通过与医疗保健领域的合作者合作，将我们的研究付诸实践。（我与三个BC和两个ON健康组织有工作关系。

The goal of this proposal is to develop a system-wide mathematical framework for improving scheduling and capacity planning decisions under uncertainty in operations and service management and apply it in the healthcare industry to achieve better service to patients (less wait times and/or achieve wait time targets) and less cost to service providers (less overtime and/or less capacity requirements). Healthcare challenges are growing in the world and timely access to healthcare is especially concerning in Canada. One way for improvement is with effective scheduling and capacity planning. This becomes more important and challenging when there is uncertainty in the system. Uncertainty is involved with patients (types, volumes), resources (availability of beds, surgery durations) and operations (length of stay in a hospital/recovery unit). I consider a system where jobs (patients) are arriving at each period and waiting in queues until they are processed in a processor (e.g., operating room (OR)) and then kept in a limited capacity storage area (e.g., recovery unit) for some time before they leave the system. There is uncertainty involved with the arrival process of jobs, processing durations and time spent in the storage area. (A subset of the same or similar type system applies to other settings in operations and service management.) Effective scheduling and capacity planning of such a system calls for a system-wide approach. However, mathematical challenges have forced researchers (including myself) to work on smaller problems in isolation for this system. I will build on my previous research in appointment and OR block scheduling to develop a system-wide mathematical framework for the system considered. I will use dynamic programming, non-smooth convex optimization methods, algorithms based on discrete convexity, simulation and process mapping. The potential benefits of this research are reduced patient wait times, improved capacity planning under uncertainty, and advancement of combined scheduling and capacity planning methodology. I am also eager to put our research in practice by working with collaborators in the healthcare sector. (I have working relationships with three BC and two ON health organizations.)