Innovative methodologies for integrated planning and scheduling and industrial applications

集成规划和调度以及工业应用的创新方法

• 批准号: 0966861
• 负责人: Marianthi Ierapetritou
• 金额: $ 34.39万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-02-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0966861&HistoricalAwards=false
• 关键词: Innovative; methodologies; integrated; planning; scheduling

0966861IerapetritouProduction planning and scheduling are decision making stages in process operations which have traditionally been practiced in a non-symbiotic manner. The full coupling of planning and scheduling models across the different temporal and spatial scales can substantially improve production operations. However, simultaneous modeling of planning and scheduling problems is currently plagued by its computational intensity, the uncertainty in model parameters and the inherently complex nature of manufacturing processes.Intellectual Merit: The PI plans on developing an integrated decision-making model that considers production planning and detailed short term scheduling to optimize the overall plant production capacity. By integrating planning and scheduling decision making levels the model becomes very complex and conventional solution methods turn out to be inefficient. She plans to develop an efficient modeling framework and advanced solution approaches based on decomposition principles to provide practical solutions to industry supplying alternative choices, but also meaningful research contributions in large-scale optimization. The main goal is to provide the decision maker solutions that are optimal in terms of production capacity and feasible in terms of detailed production scheduling. To achieve this target, the following ideas will be investigated:- Efficient ways to represent scheduling feasibility so that the integration with the planning problem will result in reasonable size model.- Efficient modeling approaches for planning and scheduling integration based on alternative ways to represent the scheduling feasibility and optimality objectives.- Solution methodologies for the integrated model based on decomposition methods.Broader Impact: The ultimate goal of this work is to optimize the production planning operations in large-scale, single-facility production plants considering the details of scheduling decisions. Realistic case studies from petrochemical, fast moving consumer goods manufacturing and chemical companies will be utilized to test and verify the results of the proposed analysis tools. The impact of the work goes beyond a specific industrial sector since the general ideas and findings can be applied or extended to different types of production facilities. The educational component of the work involves one graduate and two undergraduate students. Funding for the undergraduate students would be pursued through REU supplements. Students affiliated with program SUPER (Science for Undergraduates a Program for Excellence in Research) of Douglass College of Women will be actively involved with this project.

生产计划和调度是传统上以非共生方式实施的过程操作中的决策阶段。跨不同时间和空间尺度的计划和调度模型的充分耦合可以大大改善生产操作。然而，同时建模的规划和调度问题是目前困扰其计算强度，模型参数的不确定性和固有的复杂性质的制造processs.Intellectual Merit：PI计划开发一个综合的决策模型，考虑生产计划和详细的短期调度，以优化整体工厂的生产能力。通过集成计划和调度决策层的模型变得非常复杂，传统的解决方法变得效率低下。她计划开发一个高效的建模框架和基于分解原理的高级解决方案方法，为行业提供实用的解决方案，同时为大规模优化提供有意义的研究贡献。其主要目标是提供决策者的解决方案，是最佳的生产能力和可行的详细的生产调度方面。为了实现这一目标，将研究以下想法：-表示调度可行性的有效方法，以便与规划问题的集成将导致合理的大小模型。基于替代方法的计划和调度集成的有效建模方法，以表示调度可行性和最优性目标。更广泛的影响：这项工作的最终目标是优化生产计划的运作，在大规模的，单设施的生产工厂考虑调度决策的细节。来自石化、快速消费品制造和化学公司的实际案例研究将被用来测试和验证所提出的分析工具的结果。这项工作的影响超出了具体的工业部门，因为一般的想法和结论可以应用或扩展到不同类型的生产设施。这项工作的教育部分涉及一名研究生和两名本科生。本科生的资金将通过REU补充。道格拉斯女子学院SUPER（本科生科学研究卓越计划）项目的学生将积极参与该项目。