Doctoral Dissertation Research in DRMS: Cross-Disciplinary Analyses Using Multi-Attribute Utility Theory

这项工作的目标是研究涉及多个目标的三种特定类型的决策。第一组决定包括具有健康结果的决定。这些决定可以是医疗决定，也可以是与生活方式选择有关的决定。这些决定通常涉及寿命和整体福祉之间的权衡。第二组决策包括那些具有地理上定义的结果的决策。这是环境政策决策的一个典型特征。这些决策涉及评估许多不同区域的一个或多个因素，如果没有决策分析工具的帮助，通常太复杂而无法实际执行。第三类决策包括在竞争博弈情境下做出的决策。传统的博弈论通常只考虑这些情况的物理或金钱结果，但决策分析很好地研究了其他因素的影响，这些因素可能对玩家很重要。这三种决策类型的共同特征是，每一种决策类型都试图同时最大化或最小化多个目标。为了对这些决策进行可行性分析，必须对决策者对可能结果的偏好结构做出某些假设。目标是开发足够简单的模型，使决策易于处理，但足够详细，以准确地反映偏好。在研究的所有三种情况下，更好地理解这些决定应该如何做出将是非常有益的。

The goal of this work is to study three particular types of decisions that involve more than one objective. The first set of decisions includes those with health outcomes. These can be either medical decisions, or decisions relating to lifestyle choices. These decisions often involve tradeoffs between length of life and overall well-being. The second set of decisions includes those with outcomes that are defined geographically. This is a typical feature of environmental policy decisions. These decisions involve evaluating one or more factors over many different regions, and are often too complex to be carried out practically without the help of decision analysis tools. The third set of decisions include those made in competitive game theory situations. Traditional game theory often considers only the physical or monetary outcome of these situations, but decision analysis is well-equipped to study the effects of other factors which may be important to the players.The common feature shared by these three decision types is that each one involves trying to maximize or minimize multiple objectives simultaneously. For these decisions to be feasibly analyzed, certain assumptions must be made about the structure of decision makers' preferences over the possible outcomes. The goal is to develop models simple enough to make the decisions tractable, but detailed enough to accurately reflect the preferences. In all three situations being studied, a better understanding of how these decisions should be made would be extremely beneficial.