Development of Modeling and Optimization Tools for Hybrid Systems

混合系统建模和优化工具的开发

• 批准号: 0457379
• 负责人: Lorenz Biegler
• 金额: $ 3.22万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2009-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0457379&HistoricalAwards=false
• 关键词: Development; Modeling; Optimization; Tools; Hybrid

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.

题目：混合系统建模与优化工具的发展研究：未知信息下的优化设计是过程系统工程中的一个关键问题。该项目考虑了包含两种未知信息的公式，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合系统的建模和优化。这种系统在自然界广泛存在（特别是在生物、化学和机械应用方面），也是经济规划模式的重要组成部分。对于优化公式，这些不连续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中考虑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，企业范围优化的计划和调度模型，机械和过程工程系统中混合模型的应用。最后，本研究的结果将允许考虑具有挑战性的应用太大，不能考虑现有的优化策略。更广泛的影响：项目的更广泛的影响包括：1。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小组中建立生物信息学相关的研究活动。将建模和优化方法纳入参与大学的研究生课程iv。参与混合系统研究的本科生将通过课程中的学期项目来完成。教育计划。第五部分)。项目中开发的模型和优化算法及其结果将通过出版物、演示文稿和专门为该项目设计的网页向公众公布。共同努力将代表性不足的群体和少数民族纳入我们的研究项目将是这项提案的关键组成部分。