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.

该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集成。拟议的工作将首先解决的情况下，同时规划和调度的多产品连续工厂。在第二阶段，它将解决由陶氏化学公司提供的一个现实世界的问题，该问题涉及由必须满足一组市场需求的间歇反应器组成的地理分布式制造系统的规划和调度。 对于时间的整合，我们打算开发一个双层迭代计划，涉及解决方案的聚合MILP规划和详细的MILP调度模型。为了减少这些问题中的每一个预测的界限中的差距，将研究一组新的逻辑和混合整数切割。 对于空间积分，我们将研究一个多尺度分解方法，通过拉格朗日对偶，将纳入双层时间计划。如果成功的话，拟议的研究有可能在规划和调度领域做出重大贡献，这是实现流程工业全过程优化目标的基本组成部分。预计的一个主要成果是一种新的方法，用于整合规划和调度，以实现长期和短期生产目标的一致性和协调性，这可以转化为重大的经济节省。虽然拟议的GOALI项目将主要涉及与陶氏化学公司的合作，但也将涉及与卡内基梅隆大学高级工艺决策中心（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。这项研究的结果将被记录为案例研究，并将通过互联网提供，可能使大学和公司受益。