Interactive Identification and Optimization Using a Binary Preference Relation

This paper considers the problem in which a single decision maker must choose an element from a known nonempty choice set Y of multi-attributed elements when his preferences are uncertain. The preferences are uncertain in the sense that they are not explicitly available. The decision-maker's preferences are assumed to take the form of a binary relation on Y. We present an algorithm that requires the identification of preferences during the search process. The convergence of the adopted algorithm to a best element in Y relative to whatever preferences obtain is proved under the assumption that the identification of preferences is costless. We show that the sufficient conditions for convergence of this algorithm are weaker than the sufficient conditions for convergence of the interactive algorithm for the multiple criteria problem developed by Geoffrion, Dyer, and Feinberg.