Ranking Performances of Interval Priority Weight Estimation Methods Based on Minimum Ranges with Center Estimation in Auxiliary Models

Abstract

The advantage of the interval priority weight estimation from a crisp pairwise comparison matrix has been shown over the crisp priority weight estimation. However, the performances of estimation methods for interval priority weights diminish a little when the widths of the envisaged interval priority weights decrease with decreasing the centers. Therefore, the exploration of better estimation methods is still required. In this presentation, we propose modified estimation methods based on the minimum possible ranges by introducing center estimation to the auxiliary models. The better performances of the proposed methods over the previous estimation methods for interval priority weights are demonstrated in numerical experiments of ranking alternatives in all prepared experimental settings.