U.S.-France (INRIA) Cooperative Research: Interior Point Methods for Optimal Control and Shape Optimization

美法（INRIA）合作研究：最优控制和形状优化的内点方法

• 批准号: 9726199
• 负责人: Richard Byrd
• 金额: $ 1.5万
• 依托单位: University of Colorado at Boulder
• 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: 1998-09-01 至 2002-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9726199&HistoricalAwards=false
• 关键词: U.S.; France; INRIA; Cooperative; Research

9726199ByrdThis three-year award supports US-France cooperative research on methods for optimal control and shape optimization. The researchers are Richard Byrd from the University of Colorado, Jorge Nocedal of Northwestern University, Jean Charles Gilbert and Patrick Le Tallec of the French National Institute for Research in Informatics and Applied Mathematics (INRIA) in Rocquencourt, France. The objective of their research is to develop new algorithms and software for solving large optimal control and shape optimization problems. These problems arise in many areas of application where realistic models often involve thousands of variables and constraints. They propose to develop new interior point methods that are tailored to large, nonlinear models, and provide high quality implementation of them. Their methods will be guided by two important application areas: (1) control of an immersed vehicle in the ocean; and (2) optimal design of nonlinear structures.The US and French researchers have complementary expertise in optimal control problems with constraints and in algorithm design tailored to optimal control problems and shape optimization problems. Their collaboration will advance the development of effective software for solving application problems.

9726199 Byrd这个为期三年的奖项支持美法合作研究最优控制和形状优化的方法。 研究人员是来自科罗拉多大学的Richard Byrd，西北大学的Jorge Nocedal，法国国家信息学和应用数学研究所（INRIA）的Jean Charles吉尔伯特和帕特里克Le Tallec。 他们的研究目标是开发新的算法和软件来解决大型最优控制和形状优化问题。 这些问题出现在许多应用领域，其中现实模型通常涉及数千个变量和约束。 他们建议开发新的内点方法，为大型非线性模型量身定制，并提供高质量的实现。 他们的方法将由两个重要的应用领域指导：（1）海洋中浸没车辆的控制;（2）非线性结构的优化设计。美国和法国的研究人员在带约束的最优控制问题以及针对最优控制问题和形状优化问题的算法设计方面具有互补的专业知识。 他们的合作将推动有效软件的开发，以解决应用问题。