Multiattribute Decision Analysis based on Strict Preference Relation

Abstract

To identify multiattribute utility functions with the mutual utility independence, decision makers must specify indifference points and subjective probabilities precisely. By relaxing this exact evaluation, multiattribute value models with incomplete information have been developed. In this paper, we present a new method finding a best alternative through strict preference relations derived by questions that are not difficult to answer. For given strict preference relations, in our method alternatives satisfying the relations can be obtained by solving a mathematical programming problem with constraints representing the preference relations. If there are multiple best alternatives, we can eventually find a unique best one by solving the mathematical programming problem with additional preference constraints.