Interactive Utility Assessment in Multicriteria Decision Analysis Using Implicit Trade-off Information

Abstract

This paper introduces a methodology for the assessment of a decision-maker's utility function, based on interactions requiring relatively easy responses of the implicit trade-off type, i.e. similar to responses required in STEM or goal programming methods. The estimation of the value-function model to represent preferences is useful in ranking or pruning elements of the decision space. Inputs required from the decision-maker are, however, less demanding than the pairwise comparisons (or similar preference statements) typically required by value-function models. The methodology thus appears to be appropriate for relatively large numbers of criteria. An algorithm for implementing the proposed methodology for finite action spaces is developed and applied to examples involving up to 15 criteria.