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.

在当今竞争激烈的世界中，公司必须在满足商业可持续发展和自然环境所带来的严格限制的同时，实现其系统的高效和有效的设计和操作。这些挑战需要新颖的计算方法来处理受不确定性和非线性模型影响的复杂大规模系统。优化模型和算法在这些方法的发展中起着核心作用。提出的研究计划旨在开发系统和有效的方法来优化技术，以解决受不确定性影响的复杂过程系统工程问题，这些问题无法用现有技术令人满意地解决。主要目标是开发可处理的问题公式，以解决大量（有时是无限）可能的不确定性实现，并开发优化方法，以保证大规模复杂问题的全局最优性。