CRISP Type 1: Multi-agent Modeling Framework for Mitigating Distributed Disruptions in Critical Supply Chains

CRISP 类型 1：用于减轻关键供应链中分布式中断的多主体建模框架

• 批准号: 1638302
• 负责人: Jacqueline Griffin
• 金额: $ 50万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638302&HistoricalAwards=false
• 关键词: CRISP; Type; Multi; agent; Modeling

This Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) Type 1 grant focuses on new mathematical models and analysis methods for improving resiliency in complex human-managed systems. Stakeholders within interdependent critical infrastructure systems traditionally focus on strategies to provide resiliency in the face of single, large disruptive events. This limited focus, however, leaves supply chains vulnerable to large disruptions that arise from cascades of multiple smaller distributed events and which individually are too small to warrant stakeholders attention until it is too late. Exemplifying these features, this award supports the investigation of the drug shortage crisis within the United States for which it is the combination of events, occurring at distinct time periods and distinct levels within the pharmaceutical and health care infrastructures, along with the human responses to these events, that often leads to cascading effects and prolonged drug shortages. Current efforts to mitigate the shortages, have not been successful. The research findings will inform and contribute to the development of new policies to address this contemporary life-critical problem and to understanding in general how to create a resilient system. Understanding resilient systems is key for a 21st century that faces much adversity due to environmental change, terrorism, and globalization. In addition to the research components, educational activities and content will be developed, and publicly distributed for integration in supply chain and resiliency courses in higher education institutions. These courses will demonstrate how complex, contemporary problems can be dealt with using a transdisciplinary and transformative approach.This research seeks to drive a paradigm shift with regard to infrastructure resiliency and supply chain risk management, accounting for the critical inclusion of realistic human decision making components with information sharing and bounded rationality. This is achieved by developing a unique and transformative multi-agent modeling framework that combines mathematical modeling, realistic human behavior modeling, and game design in order to more appropriately consider human behavior and dynamics of the underlying physical, information, and social systems in critical infrastructures. This requires development of new modeling frameworks in partially observable Markov decision process (POMDP) and stochastic games, including the development of a reward function structure that is: (1) computationally tractable despite large action and state space definitions, (2) able to capture fundamental trade-offs in a supply chain with distributed disruptions, and (3) amenable to being fitted with real human decision making data obtained from automatically generated and specifically designed computer games. The outcomes of this research will be to extract and define new resiliency measures and classifications incorporating a robust characterization of stable systems and agent behavior in undisrupted multilayered networked systems with multiple realistic agent-based models of human decision makers and contrast these to system performance and agent behaviors after distributed and single extreme events.

CRISP（Critical Resilient Interdependent Infrastructure Systems and Processes）的第1类资助重点关注新的数学模型和分析方法，以提高复杂人工管理系统的弹性。相互依赖的关键基础设施系统内的利益相关者传统上关注的是在面对单一的大规模破坏性事件时提供弹性的策略。然而，这种有限的关注使供应链容易受到多个较小的分布式事件级联产生的大规模中断的影响，这些事件单独太小，以至于无法引起利益相关者的注意，直到为时已晚。举例说明这些功能，这个奖项支持在美国的药物短缺危机的调查，它是事件的组合，发生在不同的时间段和不同的层次内的制药和医疗保健基础设施，随着人类对这些事件的反应，沿着，往往导致级联效应和长期的药物短缺。目前缓解短缺的努力没有取得成功。研究结果将为制定新政策提供信息和帮助，以解决这一当代生命关键问题，并从总体上了解如何创建一个有弹性的系统。了解弹性系统是21世纪的关键，由于环境变化，恐怖主义和全球化而面临许多逆境。除了研究内容外，还将开发教育活动和内容，并公开分发，以整合高等教育机构的供应链和弹性课程。这些课程将展示如何使用跨学科和变革性的方法来处理复杂的当代问题。这项研究旨在推动基础设施弹性和供应链风险管理方面的范式转变，将现实的人类决策组件与信息共享和有限理性纳入其中。这是通过开发一个独特的和变革性的多智能体建模框架来实现的，该框架结合了数学建模，现实的人类行为建模和游戏设计，以便更恰当地考虑关键基础设施中底层物理，信息和社会系统的人类行为和动态。这需要在部分可观察马尔可夫决策过程（POMDP）和随机博弈中开发新的建模框架，包括开发奖励函数结构，即：（1）尽管有大的动作和状态空间定义，但在计算上易于处理，（2）能够捕获具有分布式中断的供应链中的基本权衡，以及（3）适合于与从自动生成和专门设计的计算机游戏获得的真实的人类决策数据相匹配。本研究的成果将是提取和定义新的弹性措施和分类，结合稳定系统和代理行为的强大表征，在不间断的多层网络系统中，具有多个现实的基于代理的人类决策者模型，并将其与分布式和单一极端事件后的系统性能和代理行为进行对比。

项目成果

Minimization of Drug Shortages in Pharmaceutical Supply Chains: A Simulation-Based Analysis of Drug Recall Patterns and Inventory Policies

• DOI: 10.1155/2018/6348413
• 发表时间: 2018-01-01
• 期刊: COMPLEXITY
• 影响因子: 2.3
• 作者: Azghandi, Rana;Griffin, Jacqueline;Jalali, Mohammad S.
• 通讯作者: Jalali, Mohammad S.