CAREER: The Effects of Centralized and Decentralized Sequential Decisions on System Performance

该学院早期职业发展（CAREER）补助金的目标是全面了解集中和分散顺序决策的直接和长期影响。个人、组织和公司经常在不确定性下做出决策。这类决定往往复杂而难以作出，其影响也难以衡量。这项研究将开发量化决策过程中产生的不确定性的方法。此外，本研究还将解决涉及顺序路由和调度的决策，并需要在一个相互关联的网络中完成多个任务。这些发现将突出多个顺序决策的影响，这些决策超越了（几乎）优化不同的复杂系统。这样的顺序决策模型提供了一个自然的框架，用于分析库存控制，销售，收入管理，路由，以及许多其他经常出现在实践中的问题。因此，本研究将为学术界提供新的基础理论成果，并为实践者提供关键的见解。此外，该奖项将促进本科生和研究生的教育和发展，他们将积极参与多个研究项目。该奖项还将有助于通过开发新的博士学位来扩大研究生课程。整合了这项研究成果的课程。在所有活动中，首席研究员寻求促进在科学和工程领域代表性不足的群体的参与。该奖项将支持两个互补的工作领域。第一种是集中决策。它的动机是先验的可能性，实现的回报可能往往远离他们的最佳期望值，它提供了一个详细的概率分析动态规划策略。具体的主题包括控制瞬态系统（包括背包问题）的极限定理，不同的地平线长度的制剂分布等价，并确定政策，导致相同的限制分布作为一个通过实施最佳政策。第二条工作路线研究分散决策。它解决了将网络结构与需要多种不同服务的自利方的路由相结合所带来的复杂性。因此，本研究将描述排队网络中的均衡路由行为，比较具有自利代理的系统的性能与由中央计划器管理的相同系统的性能，并设计旨在调整集中式和分散式解决方案的机制。

The goal of this Faculty Early Career Development (CAREER) grant is to develop a comprehensive understanding of the immediate and long-term effects of centralized and decentralized sequential decisions. Individuals, organizations and firms make decisions under uncertainty on a regular basis. Such decisions are often complex and difficult to make, and their implications are difficult to measure. This research will develop approaches that quantify the uncertainty arising during the decision-making process. In addition, this research will also address decisions that involve sequential routing and scheduling and require the completion of multiple tasks in an interrelated network. The findings will highlight the effects of multiple sequential decisions that go beyond (nearly-) optimizing different complex systems. Such sequential decision models provide a natural framework for the analysis of inventory control, queueing, revenue management, routing, and many other problems frequently arising in practice. Therefore, this research will provide new fundamental theoretical results for academics as well as key insights for practitioners. Furthermore, this award will foster the education and the development of undergraduate and graduate students who will take an active part in several research projects. This award will also help expanding the graduate curriculum through the development of new Ph.D. courses that integrate the results of this research. In all the activities, the principal investigator seeks to promote the participation of underrepresented groups in the sciences and engineering.The award will support two complementary lines of work. The first considers centralized decisions. It is motivated by the a priori possibility that the realized rewards may often be far away from their optimal expected value, and it provides a detailed probabilistic analysis of dynamic programming policies. Specific topics include limit theorems for controlled transient systems (including knapsack problems), distributional equivalences across formulations with different horizon lengths, and the identification of policies that lead to the same limiting distribution as the one obtained by implementing the optimal policy. The second line of work studies decentralized decisions. It tackles the complexity that comes from combining a network structure with the routing of self-interested parties who require multiple different services. As a result, this research will characterize equilibrium routing behaviors in queuing networks, compare the performance of a system with self-interested agents with the performance of the same system when managed by a central planner, and design mechanisms that aim to align the centralized and the decentralized solutions.