ITR/AP: Model-Based Integration of Methods for the Optimization of Process Systems

这个ITR研究媒介研究项目将把一个跨学科的研究小组，其目的将是开发一个新的建模和解决方案框架，nontrivially集成了广泛的解决方案的方法，包括数学规划，约束满足，和各种启发式算法。该框架的目标是能够有效地解决具有挑战性的工程优化问题。该小组将由来自计算机科学，运筹学和化学工程的教师和学生组成。该小组的主要目标是确定可以集成算法的原则。这些原则将成为指导集成的建模语言的基础。此外，将发展新的解决方法，用于混合模型和非凸离散/连续问题的全局优化。一种是在建模阶段利用约束逻辑编程中的思想来开发问题结构：即，通过以“全局”约束的形式编写问题，这些约束单独调用针对每个约束的特殊结构定制的算法。第二种方法是在建模和求解阶段对两种类型的算法进行根本区分：检查器和求解器。该研究将主要应用于过程系统的优化，重点是反应蒸馏系统的合成以及新产品和批量生产的集成测试。因为这些问题有离散和连续两个方面，第二个方面涉及困难的非线性，它们为结合优化和基于逻辑的方法提供了一个自然的背景。然而，这项研究将开发一种通用的方法来建模和解决方案，而不是一个专门用于过程系统应用程序。

This ITR research medium research project will put together an interdisciplinary research group whose aim will be to develop a new modeling and a solution framework that nontrivially integrates a wide class of solution methods, including mathematical programming, constraint satisfaction, and a variety of heuristic algorithms. The objective of this framework is to be able to effectively tackle challenging engineering optimization problems. The group will be composed of faculty and students from Computer Science, Operations Research and Chemical Engineering. The key goal for the group will be to identify principles according to which algorithms can be integrated. These principles will then form the basis for a modeling language that guides the integration. Furthermore, new solution techniques will be developed for hybrid models and for global optimization of nonconvex discrete/continuous problems.Two paths of integration will be investigated. One is to exploit problem structure at the modeling stage by using an idea developed in constraint logic programming: namely, by writing the problem in the form of "global" constraints that individually invoke algorithms tailored to the special structure of each constraint. A second is to make a fundamental distinction, at both the modeling and solution stage, between two types of algorithms: checkers and solvers. The research will be applied primarily to the optimization of process systems, with a focus on synthesis of reactive distillation systems and the integrated testing of new products and batch manufacturing. Because these problems have both discrete and continuous aspects, and the second involves difficult nonlinearities, they provide a natural context for combining optimization and logic-based methods. However, the research will develop a general-purpose approach to modeling and solution, rather than one that is exclusively for process systems applications.