Novel Optimization Models and Methods for Process Systems Engineering Under Uncertainty

不确定性下过程系统工程的新型优化模型和方法

• 批准号: 418411-2013
• 负责人: Li, Xiang
• 金额: $ 1.97万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=596345
• 关键词: Novel; Optimization; Models; Methods; Process

In today's highly competitive world, companies must achieve efficient and effective design and operation of their systems while satisfying stringent constraints incurred by the concerns about sustainability of business and the natural environment. These challenges require novel computational methods to handle complex large-scale systems that are subject to uncertainties and nonlinear models. Optimization models and algorithms play a central role in the development of these methods. The proposed research program targets the development of systematic and efficient approaches to optimization techniques to solve complex process systems engineering problems subject to uncertainty, which cannot be satisfactorily solved with the current technologies. The major goals are to develop tractable problem formulations to address a huge (sometimes infinite) number of possible uncertainty realizations and to develop optimization methods that can guarantee global optimality for large-scale complex problems.