SGER: Robust Optimal Real-Time Control of Multiproduct Supply Chains

据估计，美国在呼叫中心工作的人数高达300万。这与众所周知的美国经济从制造业基地向服务业基地的转变是一致的。本研究旨在探讨服务系统之动态控制，包含三大创新：升级、退订与再取。虽然每种情况下的动机都来自呼叫中心，但所获得的结果将更普遍地适用。应考虑以下问题：在市场细分之后，是否对经典的资源分配策略进行简单的修改，以减少低级别客户的等待时间，同时保证高级别客户的高质量服务？从经典分配政策中得出的见解在当今的先进系统中是否仍然有用？在控制录取率的模型中，在今天的新决策模式下，是否有简单的、可实施的政策？为了解决这些问题的具体模型的服务系统。每种模式都从理论和管理的角度提出了新的挑战。如果成功的话，洞察服务系统中的最优资源分配将提供以及打开大门，为新的探索服务系统control.The智力的优点，我们提出的研究包括检查扩展的一些经典模型在调度和准入控制。这些扩展旨在更新最新的技术水平，以涵盖服务系统中的最新创新，并回答美国当前服务经济中引入的新范式。在某些情况下，我们希望所获得的见解可以作为一个警告，防止盲目使用经典的结果，因为模型变得更加复杂。事实上，所提出的模型甚至没有提出最一般的可能，但即使到目前为止的见解是深刻的。作者继续大力追求顶尖的少数民族研究生参与他的工作。此外，其结果将提高课堂教学的应用概率和运筹学/管理，作者在康奈尔大学任教的高级课程。

Some estimates put the number of people in the U.S. that work in call centers as high as 3 million. This is consistent with the well-known shift of the U.S. economy from a manufacturing base to a service base. The proposed research is to study the dynamic control of service systems with three major innovations: upgrades, reneging, and retrials. Although the motivation in each case stems from call centers, the results obtained will be applicable more generally. The following questions are to be considered:? After market segmentation, are there simple modifications to classic resource allocation policies that can reduce waiting times for lower class customers, while guaranteeing high quality service for higher class customers?? Do the insights drawn from classic allocation policies continue to be useful in the advanced systems of today?? In models with controlled the admission rates, are there simple, implementable policies given today's new decision-making paradigms?To tackle each of these questions specific models of service systems are presented. Each model presents new challenges from both a theoretical and managerial standpoint. If successful, insights into optimal resource allocation in service systems will be provided as well as opening the door for new exploration of service system control.The intellectual merits of our proposed research include examining extensions of some of the classic models in scheduling and admission control. These extensions stand to update the state of the art to cover more recent innovations in service systems and answer new paradigms introduced in the current service economy of the United States. In some cases we expect that the insights gained can serve as a warning against blindlyusing classic results as the models become more intricate. Indeed, the proposed models are not even proposed the most general possible, yet the insights even so far are profound. The author continues to work vigorously to pursue top Minority graduate students to be involved in his work. Moreover, the results will enhance classroom instruction for advanced courses in applied probability and operations research/management that the author teaches at Cornell University.