CAREER: Deterministic Approximations in Rolling Horizon Procedures under Forecast Uncertainty

9701403瑞安，这一职业奖项的研究部分，阐述了顺序决策领域的几个重要主题。决策者经常面临着在可能无限的范围内做出关于系统的一系列决策，环境条件的固有不确定性影响着系统的状态。标准的多时段决策技术往往不足以将未来时段的预测信息与当前时段作出的决策结合起来。这项研究的重点是将一种通用的、灵活的预测方法与IQ建模为马尔可夫决策过程的滚动水平过程相结合。研究的目的是：(1)确定考虑预测不确定性的有限确定子问题的适当长度和公式；(2)评估每个近似级别对决策的长期成本的影响；(3)评估预测修正的效果。拟议的教育活动旨在通过使用积极和合作的学习策略，提高学生在本科阶段的理解和留存，并通过参与一个关于教学同行审查的项目来提高教学效果。在许多不同的情况下，在不确定的情况下，对长期(或无限)规划项目使用顺序决策。例如，电力公用事业公司必须在无限的地平线上向客户输送电力，而电力需求随着时间的推移存在不确定性。制造业企业必须根据不确定的需求估计，随着时间的推移为产能扩张分配资金。这项研究应该会对我们更好地在长期规划范围内做出决策的能力产生影响。此外，教育部分应该对工程基础设施产生积极影响，鼓励本科生进行跨学科和团队思维。

9701403 Ryan The research component of this CAREER award addresses several important topics in the area of sequential decision making. Decision makers are often faced with making a sequence of decisions about a system over a possibly infinite horizon, with inherent uncertainty in the environmental conditions influencing the system state. Standard multiperiod decision-making techniques are often inadequate in integrating forecast information for future time periods with the decision made in the current time period. This research is focused on integrating a general and flexible forecasting approach with a rolling horizon procedure that iq modeled as a Markov decision process. The research objectives are to: (1) determine appropriate lengths and formulations of the finite deterministic subproblems to account for forecast uncertainty, (2) assess the effect of each level of approximation on the long term cost of the decisions, and (3) gauge the effect of forecast revisions. The proposed educational activities are intended to improve student understanding and retention at the undergraduate level through the use of active and cooperative learning strategies, and enhance teaching effectiveness by participation in a project on the peer review of teaching. The use of sequential decision-making for long- (or infinite-) term planning projects under uncertainty arise in a number of different contexts. For example, electric utilities must deliver power to customers over an infinite horizon, with uncertainty in the demand for electricity over time. Manufacturing concerns must allocate funds for capacity expansion over time based on uncertain demand estimates. This research should have an impact on our ability to better make decisions over long planning horizons. Moreover, the educational component should have a positive impact on the engineering infrastructure, encouraging interdisciplinary and team-thinking among undergraduate students.