Discrete-Review Control of Service Processing Networks with Applications to Patient Flow Management in Emergency Departments

点击翻译按钮获取中文摘要

Control of stochastic queueing networks which are often used in modeling and analysis of service systems (e.g., hospitals, contact centers, and ride/bike sharing systems) has been the subject of extensive research in the past. The literature is predominantly concerned with continuous-time control, whereby the controller can interact with the system at any point in time. In many service settings, however, the system manager can only interact with the system at discrete and possibly long time-intervals. That is, although relevant information is becoming available, the controller cannot exercise control before the beginning of the next review time. ******The limitation of control to discrete-time or discrete-review policies often fundamentally changes the structure of the optimal control policy, making the corresponding continuous-time policy (if known) impractical and the insights from it hard to interpret. Despite applications and potential benefits, however, discrete-review control of queueing networks has remained mostly unexplored in the literature. ******The proposed research program aims to first provide fundamental insights on the impact of imposing the discrete-review limitation on the performance of dynamic control policies, and second, to develop practical and effective discrete-review policies for control of complex queueing networks. In particular, I will consider two important operational decisions, namely dynamic capacity allocation and capacity planning, and study queueing models that are mainly motivated by applications to patient flow management in Emergency Departments (EDs). Through collaboration with two large healthcare providers (Tritium Health Partners (THP) in Mississauga, ON, and New York Presbyterian (NYP) hospital in New York, NY) and using their data, the program will involve calibrating the models, estimating the performance of the proposed polices, and working towards their implementation in practice. ******An important characteristic of this research program is that it emphasises practical policies and relies on models that are informed by real-world data. Therefore, if successful, the outcome of the research can contribute to reduction of waiting times in EDs across Canada, where overcrowding is of growing concern. Further, although the proposed models are mainly motivated by applications to patient flow management, they capture dynamics and features that are present in various service systems. Therefore, it is expected that the methods and insights developed in this program will be useful and lead to further research for other service systems where continuous-time control is not feasible, due to either human-effects or high cost of interacting with the system.