Collaborative Research: Risk-Averse Stochastic Optimization
合作研究:风险规避随机优化
基本信息
- 批准号:0354500
- 负责人:
- 金额:$ 7.6万
- 依托单位:
- 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 2007-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This grant provides funding for the development of conceptually new models and solution methods for optimization of stochastic systems under high uncertainty and risk. The research will be based on the idea of integrating the theory of risk, stochastic optimization, and cutting-edge numerical techniques. It will focus on novel optimization models involving stochastic dominance constraints and risk measures in the objectives and in the constraints. This approach will capture the entire distribution of outcomes, including events of small probability but high consequences, rather than just the average performance.New solution methods will be developed that exploit the structure of the models and their probabilistic character. Models and methods for dynamic decision problems, which arise in many applications, will constitute a significant component of the project. The project has a high potential of providing a breakthrough in decision problems under high uncertainty and risk. If successful, it will provide decision-makers and analysts in many areas with novel tools for risk control. The results of the research will provide a qualitative advance in economics, finance, supply-chain management, manufacturing, military problems, telecommunication, electricity generation and distribution, and many other areas involving high uncertainty and risk.
该补助金提供资金,用于开发概念上的新模型和解决方案,以优化高不确定性和风险下的随机系统。该研究将基于整合风险理论,随机优化和尖端数值技术的想法。 它将集中在新的优化模型,涉及随机优势约束和风险措施的目标和约束。这种方法将捕捉结果的整个分布,包括小概率但后果严重的事件,而不仅仅是平均表现,将开发新的解决方法,利用模型的结构及其概率特性。在许多应用中出现的动态决策问题的模型和方法将构成该项目的重要组成部分。 该项目具有很高的潜力,为高不确定性和风险下的决策问题提供突破。如果成功,它将为许多领域的决策者和分析师提供新的风险控制工具。 研究结果将在经济、金融、供应链管理、制造、军事问题、电信、发电和配电以及许多其他涉及高不确定性和风险的领域提供质的进步。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Darinka Dentcheva其他文献
Risk-averse sequential decision problems with time-consistent stochastic dominance constraints
具有时间一致随机优势约束的风险规避顺序决策问题
- DOI:
10.1109/cdc51059.2022.9993044 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Darinka Dentcheva;Mingsong Ye;Yunxuan Yi - 通讯作者:
Yunxuan Yi
Relations between risk-averse models in extended two-stage stochastic optimization
扩展两阶段随机优化中风险规避模型之间的关系
- DOI:
10.55630/serdica.2023.49.49-76 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Darinka Dentcheva - 通讯作者:
Darinka Dentcheva
Stochastic optimization: theory and applications
- DOI:
10.1007/s10479-020-03672-y - 发表时间:
2020-07-14 - 期刊:
- 影响因子:4.500
- 作者:
Giorgio Consigli;Darinka Dentcheva;Francesca Maggioni - 通讯作者:
Francesca Maggioni
Stability and Sample-Based Approximations of Composite Stochastic Optimization Problems
复合随机优化问题的稳定性和基于样本的逼近
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:2.7
- 作者:
Darinka Dentcheva;Yang Lin;S. Penev - 通讯作者:
S. Penev
On Risk Evaluation and Control of Distributed Multi-agent Systems
- DOI:
10.1007/s10957-024-02464-9 - 发表时间:
2024-06-21 - 期刊:
- 影响因子:1.500
- 作者:
Aray Almen;Darinka Dentcheva - 通讯作者:
Darinka Dentcheva
Darinka Dentcheva的其他文献
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{{ truncateString('Darinka Dentcheva', 18)}}的其他基金
Collaborative Research: Time-Consistent Risk-Averse Control of Markov Systems
协作研究:马尔可夫系统的时间一致风险规避控制
- 批准号:
1311978 - 财政年份:2013
- 资助金额:
$ 7.6万 - 项目类别:
Standard Grant
Collaborative Research: Successive Risk-Neutral Approximations of Dynamic Risk-Averse Optimization Problems
协作研究:动态风险规避优化问题的连续风险中性逼近
- 批准号:
0965702 - 财政年份:2010
- 资助金额:
$ 7.6万 - 项目类别:
Standard Grant
AMC-SS: Collaborative Research: Dynamic Stochastic Optimization with Stochastic Ordering Constraints and Risk Functionals
AMC-SS:协作研究:具有随机排序约束和风险泛函的动态随机优化
- 批准号:
0604060 - 财政年份:2006
- 资助金额:
$ 7.6万 - 项目类别:
Standard Grant
Collaborative Research: Semi-Infinite Probabilistic Optimization
合作研究:半无限概率优化
- 批准号:
0303728 - 财政年份:2003
- 资助金额:
$ 7.6万 - 项目类别:
Continuing Grant
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