Large-Scale Nonlinear Programming

大规模非线性规划

• 批准号: 9987818
• 负责人: Jorge Nocedal
• 金额: $ 26.82万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9987818&HistoricalAwards=false
• 关键词: Large; Scale; Nonlinear; Programming

Large-Scale Nonlinear Programming Large nonlinear optimization problems arise in many importantareas of application such as climate modeling, weather forecasting,network design, and finance. An important open problem is how tosolve these problems reliably and quickly. The proposal describes a variety of new algorithms, based on barrier techniques, that promiseto be effective on problems of unprecedented size and complexity.To ensure that the new methods are robust even in the case of highill-conditioning, novel regularization techniques are proposed. AnInternet-based solver implementing the new algorithms will bedeveloped as part of this project. It will allow the engineeringand scientific communities to solve large optimization problemsautomatically using a web-based interface.

大规模非线性规划在气候建模、天气预报、网络设计和金融等许多重要的应用领域中都出现了大量的非线性优化问题。一个重要的开放性问题是如何可靠而快速地解决这些问题。该提案描述了基于屏障技术的各种新算法，这些算法有望有效地解决前所未有的规模和复杂性问题。为了保证新方法在高条件下的鲁棒性，提出了新的正则化技术。作为该项目的一部分，将开发一个基于互联网的求解器来实现新算法。它将允许工程和科学界使用基于网络的界面自动解决大型优化问题。