Open Cyberinfrastructure for Mixed-integer Nonlinear Programming: Collaboration and Deployment via Virtual Environments
用于混合整数非线性编程的开放网络基础设施:通过虚拟环境进行协作和部署
基本信息
- 批准号:0750826
- 负责人:
- 金额:$ 119.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2008
- 资助国家:美国
- 起止时间:2008-02-01 至 2013-01-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Optimization is one of the strategic technologies for cyberinfrastructure computational tools since this area deals with the selection of the "best" design or plan among many possible alternatives. Most of the challenging application problems in practice (e.g. engineering design and manufacturing, analysis of metabolic networks, portfolio investment) require the use of discrete variables (mostly 0-1 variables) to represent logic choices, as well as the handling of nonlinearities in order to accurately model the performance of physical, chemical, biological, financial or social systems. This optimization area is known as Mixed-Integer Nonlinear Programming (MINLP). MINLP is one of the most general tools for addressing deterministic optimization models, and there is now a significant optimization community that is increasingly interested in the solution and application of large-scale MINLP problems. This community is highly multidisciplinary involving operations researchers, industrial, chemical and mechanical engineers, economists, chemists and biologists. The difficulty, however, is that MINLP represents one of the most challenging optimization problems, particularly when dealing with non-convex functions, since this may give rise to local solutions. Therefore, finding the global optimum solution of large-scale MINLP models in reasonable computational times, remains a largely unsolved problem.The major objective of this proposal, which is a joint research effort between researchers at Carnegie Mellon and IBM Watson Research Center, is to address the challenge of solving practical large-scale MINLP optimization problems in reasonable computational times, and within a unique virtual collaborative environment that can bring together algorithm developers and application researchers. In order to address these challenges, the major goals of this proposal, are (a) Create a cyberinfrastructure environment for virtual collaboration for developing and collecting tools, and challenging test problems, and for disseminating open-source software; (b) Develop basic algorithms, formulations for predicting tight lower bounds, and open-source software for solving large-scale nonconvex MINLP problems; (c) Test software with challenge problems arising in real-world applications, mostly in engineering but also in biology and finance. A major outcome of this proposal will be the development of novel algorithms and open-source software for solving nonconvex MINLP optimization problems to either full global optimality or near-optimality. The research will also include the development of a variety of real-world application problems that will be documented as case studies with alternative formulations. The case studies will be developed jointly with IBM and a number of process industries. The proposed project will be conducted by a multidisciplinary team of researchers from Carnegie Mellon and IBMWatson Research Center.From a broader viewpoint, this proposal will lead to the development of a powerful virtual collaborative framework that will help to advance the state-of-the-art of MINLP optimization, and be a unique resource for researchers and industrial practitioners. This virtual framework will be used to develop and disseminate open-source software, and collect challenging test problems from a variety of different application areas. Another important feature will be the educational component, since education modules on MINLP modeling and codes will be included. The major results of this research will be disseminated through special sessions at INFORMS, conferences, and regular journal publications. We also intend to be involved in outreach activities to promote interest in mathematics through real-world test problems that arise in this project. Finally, CMU and IBM have been very active in aggressively recruiting under-represented minorities in research. For this project, investigators will actively seek to include outstanding undergraduate and graduate students to participate in our work from minorities and under-represented groups.
优化是网络基础设施计算工具的战略技术之一,因为该领域涉及在许多可能的替代方案中选择“最佳”设计或计划。实践中大多数具有挑战性的应用问题(例如工程设计和制造、代谢网络分析、投资组合)都需要使用离散变量(大多是0-1变量)来表示逻辑选择,以及按顺序处理非线性准确地模拟物理、化学、生物、金融或社会系统的性能。此优化区域称为混合整数非线性规划 (MINLP)。 MINLP 是解决确定性优化模型的最通用工具之一,现在有一个重要的优化社区对大规模 MINLP 问题的解决和应用越来越感兴趣。这个社区是高度多学科的,涉及运筹学研究人员、工业、化学和机械工程师、经济学家、化学家和生物学家。然而,困难在于 MINLP 是最具挑战性的优化问题之一,特别是在处理非凸函数时,因为这可能会产生局部解。因此,在合理的计算时间内找到大规模 MINLP 模型的全局最优解,仍然是一个很大程度上未解决的问题。该提案是卡内基梅隆大学和 IBM Watson 研究中心的研究人员的联合研究成果,其主要目标是解决在合理的计算时间内解决实际大规模 MINLP 优化问题的挑战,并在一个独特的虚拟协作环境中将算法开发人员和应用研究人员聚集在一起。为了应对这些挑战,本提案的主要目标是 (a) 创建一个用于虚拟协作的网络基础设施环境,以开发和收集工具、挑战测试问题以及传播开源软件; (b) 开发用于预测严格下界的基本算法、公式以及用于解决大规模非凸 MINLP 问题的开源软件; (c) 使用现实世界应用中出现的挑战问题来测试软件,主要是在工程领域,但也有在生物学和金融领域。该提案的主要成果将是开发新颖的算法和开源软件,用于解决非凸 MINLP 优化问题,达到完全全局最优或接近最优。该研究还将包括各种现实世界应用问题的开发,这些问题将被记录为具有替代公式的案例研究。这些案例研究将与 IBM 和许多流程工业联合开发。拟议的项目将由来自卡内基梅隆大学和 IBMWatson 研究中心的多学科研究人员团队进行。从更广泛的角度来看,该提案将导致开发一个强大的虚拟协作框架,这将有助于推进最先进的技术MINLP 优化的艺术,并成为研究人员和工业从业者的独特资源。该虚拟框架将用于开发和传播开源软件,并从各种不同的应用领域收集具有挑战性的测试问题。另一个重要功能是教育部分,因为将包括有关 MINLP 建模和代码的教育模块。这项研究的主要成果将通过 INFORMS 的特别会议、会议和定期期刊出版物进行传播。我们还打算参与外展活动,通过该项目中出现的实际测试问题来提高人们对数学的兴趣。最后,卡耐基梅隆大学和 IBM 一直非常积极地在研究中积极招募代表性不足的少数群体。对于这个项目,研究人员将积极寻求少数族裔和代表性不足群体的优秀本科生和研究生参与我们的工作。
项目成果
期刊论文数量(0)
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专利数量(0)
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Ignacio Grossmann其他文献
HYPERSCALE MODELING: MOLECULE, PROCESS, ENTERPRISE
超大规模建模:分子、过程、企业
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
André Bardow;Ignacio Grossmann - 通讯作者:
Ignacio Grossmann
A comparative study of continuous-time models for scheduling of crude oil operations in inland refineries
内陆炼厂原油作业调度连续时间模型比较研究
- DOI:
10.1016/j.compchemeng.2012.05.009 - 发表时间:
2012-09 - 期刊:
- 影响因子:0
- 作者:
Xuan Chen;Ignacio Grossmann;Li Zheng - 通讯作者:
Li Zheng
Ignacio Grossmann的其他文献
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{{ truncateString('Ignacio Grossmann', 18)}}的其他基金
World Congress of Chemical Engineering, Barcelona 2017
世界化学工程大会,巴塞罗那 2017
- 批准号:
1741750 - 财政年份:2017
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
GOALI: Optimal Design and Operation of Reliable Process Systems
目标:可靠过程系统的优化设计和运行
- 批准号:
1705372 - 财政年份:2017
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
Optimization Models for Investment, Operation and Water Management in Shale Gas Supply Chains
页岩气供应链投资、运营和水管理优化模型
- 批准号:
1437668 - 财政年份:2014
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
GOALI: Multi-scale Optimization for the Design, Capacity Planning and Operation of Power Intensive Process Networks under Uncertain Electricity Prices and Market Demands
GOALI:电价和市场需求不确定下电力密集型过程网络的设计、容量规划和运营的多尺度优化
- 批准号:
1159443 - 财政年份:2012
- 资助金额:
$ 119.9万 - 项目类别:
Continuing Grant
Multiobjective Optimization Strategies for the Design of Sustainable Biofuel Processes
可持续生物燃料工艺设计的多目标优化策略
- 批准号:
0966524 - 财政年份:2010
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
PASI On Emerging Trends in Process Systems Eng.: Sustainability, Energy, Biosystems , Multi-Scale Design Enterprise-Wide Optimization; Mar del Plata, Arg., Aug. 12-21, 2008
PASI 论过程系统工程的新兴趋势:可持续性、能源、生物系统、多尺度设计企业范围优化;
- 批准号:
0719635 - 财政年份:2007
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
GOALI: Multiscale Decomposition Techniques for the Integration of Optimal Planning and Scheduling of Batch and Continuous Multiproduct Process Systems
GOALI:用于批量和连续多产品过程系统优化规划和调度集成的多尺度分解技术
- 批准号:
0556090 - 财政年份:2006
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
Advanced Computational Models for Multistage Stochastic Optimization of Process Systems with Renewable Resources
可再生资源过程系统多级随机优化的高级计算模型
- 批准号:
0521769 - 财政年份:2005
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
Pan-American Advanced Studies Institute Program on Process Systems Engineering; Iguacu Falls; August 5-14, 2005
泛美高级研究所过程系统工程项目;
- 批准号:
0417670 - 财政年份:2005
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
Support of Foundations of Computer Aided Process Operations (FOCAPO) 2003 Conference: A View to the Future Integration of R&D, Manufacturing and the Global Supply Chain
支持计算机辅助流程操作基金会 (FOCAPO) 2003 年会议:对 R 未来集成的展望
- 批准号:
0213622 - 财政年份:2002
- 资助金额:
$ 119.9万 - 项目类别:
Standard Grant
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