Maximizing Minimum Range Methods for Interval Weight Estimation from a Given Pairwise Comparison Matrix

In order to express the vagueness of human judgement, methods for interval weight estimation from a crisp pairwise comparison matrix were proposed in Interval AHP. The interval weights estimated by the original method do not reflect well the vagueness of human judgement existing in the given pairwise comparison matrix. Then beta-relaxation of minimum widths and-gamma-relaxation of minimum weighted widths are proposed for better interval weight estimation methods. However, their qualities depend on the selection of parameters beta and gamma. To overcome this shortcoming, a parameter-free interval weight estimation method has been proposed. In this paper, we further investigate parameter-free interval weight estimation methods and examine their usefulness by numerical experiments. We show that the parameter-free methods have similar performances to beta- and gamma-relaxation methods with appropriate parameters although their accuracy scores are a little worse.