Development of Modeling and Optimization Tools for Hybrid Systems

摘要：Lorenz Biegler提案编号：0457379机构：卡内基梅隆大学题目：混合系统建模与优化工具的开发研究：未知信息下的优化设计是过程系统工程中的一项关键任务。 该项目考虑包含两种类型的未知信息的配方，即建模信息的不确定性和过程操作的可变性。 我们将应用这些配方的动态混合系统的建模和优化。这类系统广泛存在于自然界中（特别是在生物、化学和机械应用中），也是经济规划模型的重要组成部分。对于优化公式，这些不连续的决策表示通过混合整数非线性规划（MINLP），或互补约束的数学规划（MPCC）。我们的研究将考虑MINLP和MPCC问题在广泛的应用领域，我们打算开发新的优化策略。这些研究成果将被应用到广泛的应用，包括系统生物学和药物设计，规划和调度模型的企业范围内的优化，混合模型在机械和过程工程系统的应用。最后，这项研究的结果将允许考虑具有挑战性的应用程序太大，考虑与现有的优化策略。更广泛的影响：该项目的更广泛的影响是：i.建立卡内基梅隆大学、Koc大学（土耳其）和中东技术大学（土耳其）之间的合作。在卡内基梅隆大学的PSE组中建立生物信息学相关研究活动。将建模和优化方法纳入参与大学的研究生课程中。本科生参与混合系统的研究将通过课程中的学期专题来完成（见教育计划。五、项目中开发的模型和优化算法及其结果将通过出版物、演示文稿和专门为此项目设计的网页向公众提供vi。将代表性不足的群体和少数民族纳入我们的研究方案的协调一致的努力将是这项建议的一个关键组成部分。

ABSTRACTPI: Lorenz Biegler Proposal Number : 0457379Institution: Carnegie Mellon UniversityTitle: Development of Modeling and Optimization Tools for Hybrid SystemsResearch: Optimal design under unknown information is a key task in process systems engineering. This project considers formulations that incorporate two types of unknown information, uncertainty in the modeling information and variability in the operation of the process. We will apply these formulations to the modeling and optimization of dynamic hybrid systems. Such systems occur widely in nature (particular in biological, chemical and mechanical applications) and are also essential components of economic planning models. For optimization formulations, these discontinuous decisions are represented through mixed integer nonlinear programs (MINLPs), or mathematical programs with complementarity constraints (MPCC). Our research will consider both MINLP and MPCC problems over a broad set of application domains and we intend to develop new optimization strategies. These research results will be applied to broad set of applications including systems biology and drug design, planning and scheduling models for enterprise wide optimization, applications of hybrid models in mechanical and process engineering systems. Finally, the results of this research will allow consideration of challenging applications too large to be considered with existing optimization strategies. Broader Impacts:The broader impacts of the project are:i. creation of collaboration between the Carnegie Mellon University, Koc University (Turkey), and Middle East Technical University (Turkey)ii. establishment of a bioinformatics related research activity in the PSE group at Carnegie Mellon Universityiii. incorporation of the modeling and optimization methods in the graduate courses at the participating universitiesiv. participation of undergraduate students in hybrid systems research will be accomplished through term projects in the courses (see .Educational Plan. section)v. models and optimization algorithms developed in the project and the results will be made publicly available through publications, presentations and through a web page specifically designed for this projectvi. a concerted effort to include underrepresented groups and minorities into our research program will be a key component of this proposal.