CAREER: OPTIMIZATION FORMULATIONS AND ALGORITHMS FOR THE ANALYSIS AND DESIGN OF HIERARCHICAL MODULAR SYSTEMS

职业：分层模块化系统分析和设计的优化公式和算法

基本信息

批准号：
1748516
负责人：
Victor Zavala Tejeda
金额：
$ 50.24万
依托单位：
University of Wisconsin-Madison
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1748516&HistoricalAwards=false
关键词：
CAREER OPTIMIZATION FORMULATIONS ALGORITHMS ANALYSIS

项目摘要

Modularization is a pervasive organization strategy that is used by living, socio-economic, and industrial systems to cope with complexity. Modular industrial systems are built from small-scale, standardized equipment modules, which perform well-defined tasks. Standardization and size reduction enables mass fabrication and fast deployment of equipment, which accelerates experimentation and learning and ultimately leads to technology cost reductions. Modular systems enable staged (sequential) investment strategies, which provide flexibility to mitigate market and regulatory uncertainties. They also facilitate exploitation of highly dispersed resources that are deemed too expensive to centralize. The goal of this CAREER project is to develop optimization formulations and algorithms that facilitate the analysis and design of hierarchical modular systems. These capabilities will be used to design flexible combined power fertilizer systems in rural areas that produce power, ammonia, and urea from distributed resources such as wind energy, natural gas, biomass, and organic waste. Current industrial-scale process systems are highly customized and involve logistically-complex, expensive and lengthy construction phases. Identifying technologies that are suitable for modularization and determining appropriate degrees of enterprise-wide modularity can improve operational flexibility and mitigate financial risk. Large-scale industrial process systems that benefit from the economies of scale can evolve into a hybrid state in which certain functions will be performed in small modular systems that increase flexibility. To model these systems the use of hierarchical graph abstractions is proposed to provide a natural framework for analysis and optimization of the benefits of modularity. Graph abstractions enable the use of techniques to properly organize process equipment units into tightly integrated modules and can be applied recursively at higher levels where modules represent subsystems, entire production facilities, and local/regional/global supply chain hubs. Hierarchical graph structures will be exploited by combinatorial optimization and multi-stage stochastic programming techniques to derive scalable design and investment strategies that mitigate markets and regulatory risk. The educational part of this project aims to incorporate new hierarchical decision-making concepts into the engineering curriculum, make the curriculum itself more modular and develop software tools that enable the design of complex hierarchical systems using crowd-sourcing. Planned outreach activities will provide K-12 students from schools with high enrollment of underrepresented minorities with opportunities to learn about the benefits of modular decision-making and motivate them to pursue career paths in STEM fields.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.

模块化是一种普遍的组织策略，由生活，社会经济和工业系统使用来应对复杂性。模块化工业系统是由执行明确任务的小型标准化设备模块构建的。标准化和尺寸降低可以使设备的大规模制造和快速部署，从而加速了实验和学习，并最终导致技术成本降低。模块化系统实现了分阶段（顺序）投资策略，从而为减轻市场和监管不确定性提供了灵活性。它们还促进了被认为太昂贵而无法集中的高度分散资源的剥削。该职业项目的目标是开发优化配方和算法，以促进分层模块化系统的分析和设计。这些功能将用于在农村地区设计柔性的合并功率肥料系统，这些系统从分布式资源（例如风能，天然气，生物量和有机废物）产生电力，氨和尿素。当前的工业规模工艺系统是高度定制的，涉及逻辑上的复合，昂贵且冗长的建筑阶段。识别适合模块化并确定适当程度的企业范围内模块化的技术可以提高运营灵活性并减轻财务风险。从规模经济经济中受益的大规模工业过程系统可以演变为混合状态，在该状态下，将在提高灵活性的小型模块化系统中执行某些功能。为了建模这些系统，提出了层次图抽象的使用，以提供一个自然框架，以分析和优化模块化的益处。图形抽象使技术能够使用技术将工艺设备单元正确组织到紧密整合的模块中，并且可以在模块代表子系统，整个生产设施以及本地/区域/全球供应链中心的较高级别上递归应用。层次图结构将通过组合优化和多阶段随机编程技术来利用，以得出可扩展的设计和投资策略，以减轻市场和监管风险。该项目的教育部分旨在将新的层次决策概念纳入工程课程，使课程本身更加模块化，并开发软件工具，以便使用众包设计复杂的层次结构系统。计划的外展活动将为来自学校的K-12学生提供高分代表人数不足的少数群体的入学率，并有机会了解模块化决策的好处，并激励他们在STEM领域中追求职业道路。这一奖项反映了NSF的法定任务，并被视为已被视为值得通过基金会的智力优点和更广泛的影响审查标准来通过评估来支持。