Abstract

Multi-attribute decision making (MADM) methods have been widely used in the strategic planning of electric utilities for selecting the best resource strategy with regard to the chosen attributes. In many MADM problems, however, the information available to the decision-maker (DM) is often imprecise due to inaccurate attribute measurements and inconsistent priority judgments. This paper presents an interval-based MADM approach in support of the decision making process with imprecise information. The proposed MADM methodology is based on the model of lineal additive utility function but extends the problem formulation with the measure of composite utility variance. Its main contribution is to help the DM gain insight into how the imprecise data may affect the choice toward the best solution and how a set of acceptable alternatives may be identified with certain confidence. Sample case studies are provided to illustrate the concepts introduced in this paper.

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