A Comprehensive Approach to Chemical Process Scheduling Problems

工业化工加工的成功需要高效的管理能力和快速适应市场变化的能力。大量的约束、不断扩大的操作范围、时间和效率压力，以及离散决策所隐含的组合复杂性，使得调度和计划问题难以解决。这项研究将为开发过程调度工具奠定基础，这些工具基于严格的优化方法，对故障具有鲁棒性，易于在工业环境中使用，可以快速与企业数据库集成，并且可以解决非常大且高度约束的调度和计划问题。严格的优化方法提供了可用的最佳可实现性能的估计，并且在最佳情况下，它们生成了一个可证明是给定工业场景的最佳调度。该项目的重点是提供必要的方法和信息，以理解和控制系统中过程性能的关键组件，该系统具有足够的灵活性，可以合并技术进步，并且设计用于考虑调度和计划功能将随着时间不断发展的事实。要使用的原型系统是基于这样一个前提，即所有这样的系统都可以以模块化的方式进行查看。本研究的目的是：(1)开发一种专门针对排序考虑的公式，该公式将补充现有的公式，并能够相当详细地处理一系列过程；(2)开发一种有效的方法，通过引入从问题物理学中推导出的强不等式来加强调度问题的公式；(3)开发针对调度和规划问题的大规模整数规划解决方案，并足以解决长时间尺度的问题；(4)集成符号推理和数学规划方法，以减少使用复杂系统所需的训练，并减轻在组合优化问题上独家使用优化方法所固有的鲁棒性问题。

Abstract - Pekny - 9402948 Industrial chemical processing success requires efficient management of capacity and the ability to quickly adapt to changes in the marketplace. A large number of constraints, the increasing scope of operations, time and efficiency pressures, and the combinatorial complexity implied by discrete decisions make scheduling and planning problems difficult to solve. This research will lay the foundation for developing process scheduling tools that are based on rigorous optimization methods, are robust to failure, easy to use in an industrial environment, can be quickly integrated with corporate databases, and can address very large and highly constrained scheduling and planning problems. Rigorous optimization methods provide an estimate of the best achievable performance available and, in the best case, they produce a schedule that is provably optimal for a given industrial scenario. The focus for this project is to provide the methodology and information necessary for understanding and controlling the critical components of process performance in a system that is sufficiently flexible to incorporate technological advances and that is designed to account for the fact that the scheduling and planning function will continue to evolve over time. The prototype system to be used is based on the premise that all such systems can be viewed in a modular fashion. The objectives of the research are: (1) development of a formulation specifically tuned to sequencing considerations that will complement existing formulations and be able to address a range of processes in considerable detail, (2) development of an efficient means to strengthen the formulation of scheduling problems through the introduction of strong inequalities derived from problem physics, (3) development of large scale integer programming solutions capability specific to scheduling and planning problems and sufficient to address long time scales, and (4) integration of symbolic reasoning and mathematical programming methods to reduce the training required to use a sophisticated system and mitigate the robustness problems inherent with exclusive use of optimization methods on combinatorial optimization problems.