Collaborative Research: Risk-Averse Stochastic Optimization

该基金为高不确定性和高风险随机系统优化的概念性新模型和解决方法的开发提供资金。该研究将基于整合风险理论、随机优化和前沿数值技术的思想。它将侧重于涉及随机优势约束和目标和约束中的风险度量的新型优化模型。这种方法将捕获结果的整个分布，包括小概率但后果高的事件，而不仅仅是平均表现。新的解决方法将开发利用模型的结构和它们的概率特征。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。该项目具有很大的潜力，为解决高不确定性和高风险的决策问题提供了突破口。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。

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.