Policy-Robust Processing Networks: Characterization and Design

策略稳健的处理网络：表征和设计

• 批准号: 2139566
• 负责人: Itai Gurvich
• 金额: $ 48.62万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2139566&HistoricalAwards=false
• 关键词: Policy; Robust; Processing; Networks; Characterization

This award will contribute to the nation's economic competitiveness by improving the design and operation of stochastic processing networks. Stochastic processing networks, consisting of interconnected processing nodes with some flexibility to manage their own schedules, arise in a variety of settings, including many service systems and some manufacturing systems. The fact that arrival times, processing times, and routes through the network may not be predictable with certainty makes these networks particularly difficult to analyze. This award supports research into conditions for global stability of these networks where each node in the network has some autonomy and independent scheduling authority; that is, the larger network does not operate under a centralized scheduler. Stability of the network ensures that any entity entering the network will eventually be processed and leave the network. The project studies stochastic processing networks incorporating renewal arrival processes, service times with general distributions, Bernoulli routing, and multiple classes of jobs at each station. A primary interest is the global stability of these networks, i.e., stability of the network as a whole when each individual node operates under its own non-idling scheduling policy. In these networks, control is distributed, rather than being determined by a central scheduler. The major goal of this research is the development of a new framework for global stability that can support the design of operating rules that allow fairly general decentralized control. The project will lead to a better understanding of the design of robust complex networks. The techniques employed involve ideas from fluid and diffusion approximations to queueing networks, along with notions from robust optimization.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.

该奖项将通过改善随机处理网络的设计和运作来促进美国的经济竞争力。 随机处理网络由互连的处理节点组成，具有一些灵活性来管理自己的时间表，这些节点在各种设置中都出现，包括许多服务系统和某些制造系统。 到达时间，处理时间和通过网络的路线的事实可能无法确定性预测，因此这些网络特别难以分析。 该奖项支持对这些网络的全球稳定性条件的研究，在这些网络中，网络中的每个节点都具有某些自治和独立的调度授权；也就是说，较大的网络不在集中调度程序下运行。网络的稳定性确保进入网络的任何实体最终都将被处理并离开网络。 项目研究随机处理网络结合了续签到达流程，带有一般分布的服务时间，伯努利路由以及每个站点的多个工作。主要的兴趣是这些网络的全球稳定性，即，当每个节点在其自己的非上限调度策略下运行时，网络的整体稳定性。 在这些网络中，控制是分布的，而不是由中央调度程序确定。这项研究的主要目标是开发一个新的全球稳定框架，该框架可以支持操作规则的设计，该规则允许相当普遍的分散控制。 该项目将更好地理解健壮的复杂网络的设计。所采用的技术涉及从流体和扩散近似到排队网络的想法，以及强大优化的概念。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响来通过评估来支持的。

项目成果

Policy robustness in queueing networks

排队网络中的策略稳健性

• DOI: 10.1007/s11134-022-09776-5
• 发表时间: 2022
• 期刊: Queueing Systems
• 影响因子: 1.2
• 作者: Gurvich, Itai;Hasenbein, John J.
• 通讯作者: Hasenbein, John J.