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.

[966861]生产计划和排程是流程操作中的决策阶段，传统上以非共生的方式进行。跨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，规划与调度问题的同步建模目前受到计算量大、模型参数不确定性和制造过程固有复杂性等问题的困扰。智力优势：PI计划开发一个综合决策模型，考虑生产计划和详细的短期调度，以优化整个工厂的生产能力。由于集成了计划和调度决策层，模型变得非常复杂，传统的求解方法效率低下。她计划开发一个高效的建模框架和基于分解原理的先进解决方法，为提供替代选择的行业提供实用的解决方案，同时也为大规模优化提供有意义的研究贡献。主要目标是为决策者提供生产能力最优、详细生产调度可行的解决方案。为了实现这一目标，将研究以下思路：-有效地表示调度可行性的方法，以便与规划问题的集成将产生合理的规模模型。-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。-基于分解方法的集成模型求解方法。更广泛的影响：这项工作的最终目标是在考虑调度决策细节的情况下，优化大型、单设施生产工厂的生产计划操作。来自石化、快速消费品制造和化工公司的实际案例研究将用于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特定的工业部门，因为一般的想法和发现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。本科学生的经费将通过REU补助款筹措。道格拉斯女子学院SUPER（本科生科学卓越研究项目）项目的学生将积极参与本项目。