Decision Trees with Single and Multiple Interval‐Valued Objectives

Important to decision making is recognition of what today's decisions have on future options, and an oft‐used tool to aid in this problem is the decision tree. This paper addresses situations in which uncertainty arises in the objectives associated with different sequential decision paths and provides a decision tree for uncertain parameters where only bounds, not distributions, are known. Single‐ and multiple‐objective interval‐valued decision trees are introduced. Interval arithmetic is used for the decision tree rollback process. To address the difficulty of an interval‐valued comparison of alternatives, several decision rules, as well as a probabilistic approach, are discussed in the decision tree context. The interval‐valued decision trees are deployed in a simple maintenance, repair, and overhaul decision‐making illustration.