CAREER: Online Optimization and Control of Real-Time Transportation Systems

职业：实时交通系统的在线优化和控制

• 批准号: 9733929
• 负责人: Athanasios Ziliaskopoulos
• 金额: $ 23.5万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-06-01 至 2003-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9733929&HistoricalAwards=false
• 关键词: CAREER; Online; Optimization; Control; Real

Abstract Proposal: 97-33929 Northwestern University PI: Athanasius Ziliaskopoulos "CAREER: On-line Optimization and Control of Real-Time Transportation Systems" This CAREER award supports research concerned with the problem of on-line control and optimization of the operations of a real-time dynamic and stochastic transportation system. The motivation for this research is two-fold: to use to use new technological advances to improve the control and management of transportation operations; and to fill the gap created by the lack of algorithms that can use these technologies to improve the efficiency of transportation operations. In addition to the research problems initiated by the technological advances, several fundamental educational issues are raised: In general, students and practicing transportation engineers do not have sufficient technical background to fully appreciate the complex behavior of stochastic and dynamic systems and the knowledge to exploit the potential of real-time data. This is partly due to training that has traditionally been limited to the concepts of equilibrium, steady state average system behavior and determinism. Educators are faced with the challenge of developing innovative pedagogical material and methodologies that convey the fundamental principles of dynamic and stochastic systems, given the limited background of typical engineering students. The main research and educational objectives are: to analyze the operations of real-time transportation systems and identify their properties; to develop closed form analytical formulations by exploiting their special properties and to explore various exact and heuristic solution approached, optimality conditions for exact algorithms and performance bounds for heuristic approaches; and to develop new pedagogical tools that will enable students to understand the fundamental principles of dynamic and stochastic systems. To achieve these objectives, concepts from four major areas will be utilized: stochastic programming, stochastic optimal control, process control, and Markovian decision processes.

摘要建议：97-33929西北大学PI：Athanasius Ziliaskopoulos“职业：实时运输系统的在线优化和控制”该职业奖支持与实时动态和随机动态和随机运输系统运营的在线控制和优化的研究。 这项研究的动机是两个方面：用于利用新技术进步来改善运输运营的控制和管理；并填补缺乏可以使用这些技术来提高运输操作效率的算法所产生的空白。 除了技术进步引发的研究问题外，还提出了一些基本的教育问题：总的来说，学生和执业运输工程师没有足够的技术背景来充分欣赏随机和动态系统的复杂行为以及知识来利用实时数据的潜力。 这部分是由于传统上仅限于平衡，稳态平均系统行为和确定性的概念的训练。 鉴于典型的工程专业的学生的背景有限，教育者面临着开发创新的教学材料和方法的挑战。 主要的研究和教育目标是：分析实时运输系统的运营并确定其特性；通过利用其特殊特性并探索各种精确和启发式解决方案的方法来开发封闭形式的分析公式，以实现启发式方法的精确算法和性能界限的最佳条件； 并开发新的教学工具，以使学生能够了解动态和随机系统的基本原理。 为了实现这些目标，将利用来自四个主要领域的概念：随机编程，随机最佳控制，过程控制和马尔可夫决策过程。