Logarithmic Conversion Approach to the Estimation of Interval Priority Weights from a Pairwise Comparison Matrix

Abstract

An alternative method for the estimation of interval priority weights in Interval AHP is proposed. The proposed method applies the logarithmic conversion to components of the pairwise comparison matrix and obtains logarithmically-converted interval priority weights so as to minimize the sum of their widths. The logarithmically-converted interval priority weights are estimated as an optimal solution of a linear programming problem. The interval priority weights are obtained by the antilogarithmic conversion of the optimal solution and by the normalization. Numerical experiments are conducted to demonstrate the advantages of the proposed estimation over the conventional estimation.