Service Systems with Outbound Work and Blending

该奖项的研究目标是开发新的模型和控制机制，忠实地描述当代服务系统，如同时处理入站和出站工作的联系中心和医疗保健系统。将特别关注在时变或随机环境中由同一组代理处理这两种类型作业的系统，这一过程称为“混合”。这两类工作之间最显著的区别是，入站工作通常是从外部到达的，因此管理层无法直接控制到达率，而出站工作的到达过程是由系统本身产生的，因此其到达率基本上是受控制的。可以利用安排出站到达的灵活性来提高绩效，特别是减少与进站工作到达过程相关的变异性。然而，出站工作也引入了新类型的实践和分析挑战，这是专门为入站工作服务的系统中不存在的。例如，现代联系中心使用自动拨号器来生成呼出呼叫。在混合服务池中，当被叫客户应答时，很可能所有工程师都很忙，因此呼叫被挂断。在医疗保健环境中，除了预定的预约(出院病人)外，接受直接就诊(入站病人)的诊所在做出人员配备和日程安排决策时必须考虑出院病人的缺席和迟到情况。因此，仅处理入站工作的系统已知的现有结果和见解不会直接扩展到也处理出站工作的系统。将解决的具体问题包括：1)如何设计一个处理这两类工作的系统，例如，何时使用混合更好，以及何时由专用服务池处理每种类型的工作更好。2)面对时变的或随机的进货工作到达率，如何最大限度地利用灵活性。3)在给定的入站和出站客户服务水平约束下，如何为混合服务池配备人员，以实现所需的出站工作吞吐量。4)如何实时路由客户和调度代理。如果成功，这项研究将开发新的方法和工具来设计和控制具有外发工作和在非固定环境中混合的大型服务系统。由于精确分析非常困难，因此将证明新的多服务器高流量限制，并显示提供有效的近似值。渐近分析的一个具有挑战性的特点是，出站工作的生成发生在快速的时间尺度上，因此需要对繁忙的流量进行精细的分析。这一性质，加上入境到达率的非平稳性和不确定性，带来了技术上的复杂性，使得有限的论点很难推导出来。成功的结果将导致新类型的有用的渐近技术和洞察力，这些技术和见解也可能应用于其他环境。

The research objective of this award is to develop new models and control mechanisms that faithfully describe contemporary service systems, such as contact centers and healthcare systems, which handle inbound and outbound work simultaneously. Special attention will be given to systems that process the two types of jobs by the same group of agents, a process referred to as "blending," in time-varying or random environments. The most significant difference between the two types of jobs is that inbound work typically arrives exogenously, so that management has no direct control on the arrival rate, whereas the arrival process of outbound work is generated by the system itself, and its arrival rate is therefore mostly controlled. The flexibility in scheduling outbound arrivals can be exploited to improve performance, and in particular, to reduce the variability associated with the arrival process of inbound work. However, outbound work also introduces new types of practical and analytical challenges that do not exist in systems that are dedicated to serving inbound work. For example, modern contact centers employ automatic dialers to generate outbound calls. In a blended service pool, it is then highly possible that all agents are busy by the time a called customer replies, so that the call is dropped. In healthcare settings, a clinic that accepts walk-ins (inbound patients) in addition to scheduled appointments (outbound patients), must take into account no-shows and late arrivals of outbound patients when making staffing and scheduling decisions. Therefore, existing results and insights that are known for systems that handle only inbound work, do not directly extend to systems that process also outbound work. Specific questions that will be addressed are: 1) How to design a system that processes the two types of jobs, e.g., when is it better to use blending, and when is it preferable to handle each type of work by a dedicated service pool. 2) How to best utilize the flexibility in face of time-dependent, or stochastic arrival rates of inbound work. 3) How to staff blended service pools so as to achieve a desired throughput rate of outbound work, subject to given service-level constraints for both inbound and outbound customers. 4) How to route customers and schedule agents in real time. If successful, this research will develop new methods and tools to design and control large service systems with outbound work and blending in non-stationary settings. Since exact analysis is prohibitively hard, novel many-server heavy-traffic limits will be proved and shown to provide effective approximations. A challenging characteristic of the asymptotic analysis is that the generation of outbound work takes place in a fast time scale, therefore requiring refined heavy-traffic analysis. This property, in addition to the non-stationarity and uncertainty regarding inbound arrival rates, presents technical complications that make limiting arguments hard to derive. Successful results will lead to new types of useful asymptotic techniques and insights which can potentially be applied in other settings as well.