GOALI: Multiscale Decomposition Techniques for the Integration of Optimal Planning and Scheduling of Batch and Continuous Multiproduct Process Systems

GOALI：用于批量和连续多产品过程系统优化规划和调度集成的多尺度分解技术

• 批准号: 0556090
• 负责人: Ignacio Grossmann
• 金额: --
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0556090&HistoricalAwards=false
• 关键词: GOALI; Multiscale; Decomposition; Techniques; Integration

This GOALI grant provides funding for the development of multiscale decomposition techniques that will allow the temporal and spatial integration of planning and scheduling problems that arise in the process industry. The proposed work will initially address the case of simultaneous planning and scheduling of multiproduct continuous plants. In the second phase, it will address a real-world problem provided by The Dow Chemical Company that deals with planning and scheduling of geographically distributed manufacturing systems consisting of batch reactors that must satisfy demands for a set of markets. For the temporal integration we intend to develop a bilevel iterative scheme that involves the solution of aggregate MILP planning and detailed MILP scheduling models. To reduce the gap in the bounds predicted by each of these problems, a novel set of logic and mixed-integer cuts will be investigated. For the spatial integration we will investigate a multiscale decomposition approach through Lagrangean duality that will incorporate the bilevel temporal scheme. If successful, the proposed research has the potential of making significant contributions in the areas of planning and scheduling, which are basic building blocks for achieving the goal of Enterprise-wide Optimization in the process industry. A major result that is expected is a new methodology for integrating planning and scheduling in order to achieve consistency and coordination in long and short term production targets, which can translate into major economic savings. While the proposed GOALI project will primarily involve collaboration with Dow Chemical, it will also involve potential collaboration and dissemination of the research results with the petroleum, chemical and engineering/software companies that are members of the Center for Advanced Process Decision-making (CAPD) at Carnegie Mellon. The findings of this research will be documented as case studies that will be made available through the internet, potentially benefiting universities and companies.

GOALI 赠款为多尺度分解技术的开发提供资金，该技术将允许过程工业中出现的规划和调度问题的时间和空间整合。拟议的工作将首先解决多产品连续工厂同时规划和调度的情况。在第二阶段，它将解决陶氏化学公司提供的一个现实问题，该问题涉及地理分布式制造系统的规划和调度，该系统由必须满足一系列市场需求的间歇反应器组成。 对于时间集成，我们打算开发一种双层迭代方案，其中涉及聚合 MILP 规划和详细 MILP 调度模型的解决方案。为了减少每个问题所预测的边界差距，将研究一组新颖的逻辑和混合整数切割。 对于空间积分，我们将研究通过拉格朗日对偶性的多尺度分解方法，该方法将结合双层时间方案。如果成功，拟议的研究有可能在规划和调度领域做出重大贡献，这是实现流程工业企业范围优化目标的基本组成部分。预期的主要成果是一种整合规划和调度的新方法，以实现长期和短期生产目标的一致性和协调，这可以转化为重大的经济节约。虽然拟议的 GOALI 项目将主要涉及与陶氏化学的合作，但它也将涉及与高级工艺决策中心 (CAPD) 成员的石油、化学和工程/软件公司的潜在合作和研究成果的传播在卡内基梅隆大学。这项研究的结果将被记录为案例研究，并通过互联网提供，可能使大学和公司受益。