Collaborative Research: Risk-Averse Stochastic Optimization

这笔赠款为开发概念上的新模型和求解方法提供资金，用于高不确定性和高风险下的随机系统的优化。这项研究将基于整合风险理论、随机优化和尖端数值技术的思想。它将集中于新的优化模型，包括随机优势约束以及目标和约束中的风险度量。这种方法将捕捉结果的整个分布，包括小概率但高后果的事件，而不仅仅是平均性能。将开发新的求解方法，以利用模型的结构及其概率特征。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。该项目在高不确定性和高风险的决策问题上具有很高的突破潜力。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高风险的领域取得质的进展。

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.