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GOALI: Short-term Scheduling Under Uncertainty: A Robust Optimization Framework

GOALI：不确定性下的短期调度：鲁棒优化框架

基本信息

批准号：
0355336
负责人：
Christodoulos Floudas
金额：
$ 9万
依托单位：
Princeton University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2004
资助国家：
美国
起止时间：
2004-08-15 至 2008-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0355336&HistoricalAwards=false
关键词：
GOALI Short term Scheduling Under

项目摘要

The primary objective of this Grant Opportunity for Academic Liaison with Industry (GOALI) research project is to develop theoretical, algorithmic and computational techniques for addressing the short-term scheduling under uncertainty in chemical processes. The following specific aims will be investigated. In Aim 1, a novel robust optimization framework for addressing uncertainty issues will be studied. In Aim2, the application of the robust optimization framework in Aim 1 to the short-term scheduling of batch and continuous chemical processes which feature multiproduct, multipurpose plants with demands at intermediate due dates and a large number of uncertain parameters will be investigated.The work will result in novel robust optimization models that will form the foundation for addressing the uncertainly in the short-term scheduling of chemical systems. A unique contribution is that this framework can address uncertainly issues for models that contain a large number of uncertain parameters. These robust optimization formulations for mixed-integer linear and nonlinear models have applications in a variety of disciplines, and hence this is a generic component in the proposed work. These theoretical and algorithmic developments will be complemented with industrial case studies and will benefit from our collaboration with the research group at ATOFINA Chemicals Inc. These industrial case studies will be used to validate the robust optimization framework for short-term scheduling chemical systems under uncertainty.

该研究项目的主要目标是开发理论，算法和计算技术，用于解决化学过程中不确定性下的短期调度问题。将研究以下具体目标。在目标1中，将研究用于解决不确定性问题的新的鲁棒优化框架。在目标2中，将目标1中的鲁棒优化框架应用于具有多产品特性的间歇和连续化工过程的短期调度，本文将研究具有中间交货期需求和大量不确定性参数的多用途电厂。这项工作将产生新的鲁棒优化模型，为解决短期内的不确定性奠定基础。化学系统的术语调度。一个独特的贡献是，这个框架可以解决模型，包含大量的不确定参数的不确定性问题。混合整数线性和非线性模型的这些鲁棒优化配方在各种学科中有应用，因此这是一个通用的组成部分，在拟议的工作。这些理论和算法的发展将与工业案例研究相辅相成，并将受益于我们与阿托菲纳化学公司研究小组的合作。这些工业案例研究将用于验证不确定性下的短期调度化学系统的鲁棒优化框架。