The advantage of the interval priority weight vector estimated from a crisp pairwise comparison matrix over the estimated crisp priority weight vector has been demonstrated. Various methods for estimating interval priority weights have been proposed and compared by numerical experiments based on their performances to explore better estimation methods. The estimation methods based on minimum possible ranges have shown their good performances. However, the performances of those methods deteriorate to a certain extent when the widths of the assumed true interval priority weights decrease with decreasing the centers. Therefore, the exploration of better estimation methods has been continued. This paper proposes modified methods based on the minimum possible ranges by incorporating the center estimations in submodels. Numerical experiments about the estimation accuracy of interval priority weights and the accuracy of ordering alternatives are conducted. The results of the numerical experiments show that one of the proposed methods stably performs well.