Development of Modeling and Optimization Tools for Hybrid Systems

摘要：Lorenz Biegler提案编号：0457379机构：卡内基梅隆大学标题：混合系统建模和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的关键任务。本项目考虑了包含两种未知信息的配方，即建模信息中的不确定性和过程操作中的可变性。我们将把这些公式应用于动态混杂系统的建模和优化。这种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，这些不连续的决策通过混合整数非线性规划(MINLP)或具有互补约束的数学规划(MPCC)来表示。我们的研究将在广泛的应用领域同时考虑MINLP和MPCC问题，并打算开发新的优化策略。这些研究成果将应用于广泛的应用，包括系统生物学和药物设计，用于企业范围优化的计划和调度模型，以及混合模型在机械和过程工程系统中的应用。最后，这项研究的结果将允许考虑具有挑战性的应用程序，这些应用程序太大，无法用现有的优化策略来考虑。更广泛的影响：该项目的更广泛的影响是：i.在卡内基梅隆大学、Koc大学(土耳其)和中东技术大学(土耳其)之间建立合作在卡内基梅隆大学的PSE小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。本科生参与混合系统研究将通过课程中的学期项目来完成(见教育计划。五.在项目中开发的模型和优化算法，其结果将通过出版物、演示文稿和专门为该项目设计的网页向公众公布。将代表性不足的群体和少数族裔纳入我们的研究计划的协调努力将是这项提议的关键组成部分。

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.