Multiplicity based algorithms for processing group multi-criteria expert assessments

Abstract

Abstract The paper discusses a new approach to the processing of verbal assessments, which express the opinions of experts on many criteria. The algorithm for verbal analysis of multi-feature objects expert assessments is proposed for identifying subgroups of experts with agreed opinions. It is proposed to use the multiplicity indices of multisets to calculate the coefficient of consistency. It is also proposed to use jointly the coefficients of consistency values to assess the consistency of the experts subgroups on one feature, and strive for the total maximization of the coefficients of consistency for all features. The complexity of the proposed algorithm is estimated. The results of calculations for the problem of choosing the best science-intensive technology are presented.