Efficacy Analysis of Ratios from Pairwise Comparisons

Abstract

The true pairwise comparison matrix is simulated and used as a benchmark for evaluating different priority vectors derived from a decision maker’s pairwise comparison matrix. The accuracy of the decision maker’s comparisons are progressively improved until they emulate the true values. Using four different distance measures to evaluate five different methods of deriving priorities, the geometric mean, normalized column mean, and right eigenvector techniques are more accurate. All methods exhibit rare reversals in accuracy as the comparison values approach the true values.