CAREER: Improving Service Systems through Real-time and Delayed Information

该学院早期职业发展计划（CAREER）奖支持旨在通过使服务提供商能够有效地向客户传播有关延迟的信息来减少关键服务拥堵的基础研究。 这项研究将通过更好地获得医疗保健和紧急资源以及减少城市交通拥堵来促进国民健康和繁荣。 通过智能手机应用程序和显示消息技术提供真实的时间信息，彻底改变了许多服务系统与客户互动的方式。 该项目将促进了解如何利用这些信息来改善这些服务的提供和获取。 该教育计划包括有针对性的推广工作，以扩大在工程研究中代表性不足的群体的参与。该项目将研究向潜在客户提供系统状态延迟信息的嵌入式网络。 研究的目的是提供严格的近似性能的系统。 本研究将结合多项logit模型选择模型来模拟指数模型和一般模型中的客户到达行为。 流体极限和扩散近似将被用来模拟拥挤的队列，预期的客户行为将最严重地影响排队动态。 有限容量的决策模型也将在延迟信息的背景下进行研究。 近似值将通过模拟以及与现实世界的交通系统和医院急诊部门的观测数据进行比较进行评估。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Faculty Early Career Development Program (CAREER) award supports fundamental research intended to reduce congestion in critical services by enabling service providers to effectively disseminate information about delays to their customers. This research will advance the national health and prosperity by enabling better access to healthcare and emergency resources and reducing congestion in urban mobility. The availability of real time information through smartphone apps and display message technology has revolutionized the way many service systems interact with their customers. This project will advance the understanding of how such information can be used to improve the availability and accessibility of these services. The educational plan includes targeted outreach efforts to broaden participation of underrepresented groups in engineering research.This project will study queueing networks in which delayed information on system state is offered to potential customers. The research objective is to provide rigorous approximations of the performance of such systems. The research will incorporate a multinomial logit model choice model to emulate customer arrival behavior in exponential and general queueing models. Fluid limit and diffusion approximations will be used to model congested queues, where anticipated customer behavior will most heavily influence queueing dynamics. Finite capacity queueing models will also be studied in the context of delayed information. The approximations will be assessed via simulation as well as comparisons with observational data from real-world transportation systems and hospital emergency departments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.