Presidential Young Investigator Award: Parallel Algorithms for Integer and Mixed Integer Nonlinear Programs Arising in the Management and Design of Chemical Processes

广泛的化工过程工程问题 包括系统化工艺设计、改造设计、批量生产等。 调度、生产计划、设施布局和工厂启动 可以自然地建模为混合整数非线性规划 （MINLP）。 虽然已经出版了大量的模型 针对各种具体情况， MINLP方法受到限制，因为传统的解决方案 技术仅对有限大小的模型有效。 一个 这项长期研究计划的重要目标是 开发求解MINLP的高度并行算法。 在 特别是，这项研究旨在能够使用数百个 强大的处理器，大大扩展了 MINLP的可处理性。 解决方案的急剧增加 能力对于整合多个目标至关重要， 将逼真的物理特性、灵活性和鲁棒性融入工程设计中 设计和运营模式。 三个重要问题必须 在开发有效的并行MINLP的过程中， 算法是：（1）系统开发的问题 结构（2）处理器之间的工作负荷的划分，以及 (3)利用同时可用的信息， 提高算法性能。 理解这些问题的核心 问题是专用并行算法的发展 性能 理解这些问题的核心是 开发专用并行算法， 结构化整数规划 研究将沿着沿着两条互补的路径进行：（1） 通用并行MINLP算法的发展（2） 开发专用并行算法， 结构化整数规划 这两条道路的根本目标是 学习如何有效地使用大量的并行 同时利用问题的特定特征。

A broad range of chemical process engineering problems including systematic process design, retrofit design, batch scheduling, production planning, facility layout, and plant startup may be naturally modeled as mixed integer nonlinear programs (MINLP). Although a large number of models have been published for a variety of specific situations, practical application of MINLP methods has been limited because conventional solution techniques are effective only on models of limited size. An important goal of this long term research program is the development of highly parallel algorithms for solving MINLP. In particular, this research seeks to be able to use hundreds of powerful processors to substantially extend the range of tractability for MINLP. The dramatic increase in solution capability is critical in incorporating multiple objectives, realistic physics, flexibility, and robustness into engineering design and operation models. Three important issues that must be addressed in the course of developing effective parallel MINLP algorithms are: (1) the systematic exploitation of problem structure (2) the partitioning of the workload among processors and (3) the utilization of concurrently available information to improve algorithm performance. Central to understanding these issues is the development of special purpose parallel algorithm performance. Central to understanding these issues is the development of special purpose parallel algorithms for highly structured integer programs. Research will proceed along two complementary paths: (1) development of general purpose parallel MINLP algorithms (2) development of special purpose parallel algorithms for highly structured integer programs. The underlying goal of both paths is to learn how to effectively use massive amounts of parallelism while at the same time exploiting problem specific features.