Skip to Main Content
Decision tree analysis is a formal methodology by which complex decision problems can be decomposed into sequences of contemplated decisions (or acts) and their uncertain consequences (or events). The analysis is naturally and conveniently depicted in the form of a tree, where the branches emanating from a given node represent alternative acts or events. Anticipated cash flows and probabilities are associated with appropriate branches of the tree, and an optimal strategy may be defined as that path that maximizes expected monetary gain. The concept of risk aversion may be introduced by means of a preference function, which quantitatively represents the decision-maker's attitudes toward risks. These ideas will be explored in greater depth and clarified by example in ensuing sections.
Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.