Notice of Retraction A multiple attribute evaluation method based on improved uncertain linguistic hybrid geometric mean operator

Abstract

The aggregation of uncertain linguistic variables in uncertain linguistic multiple attribute evaluation is researched in this paper. To overcome the error of the model used in the literature to compare and sequence every two uncertain linguistic variables, a new model that can accurately calculate the possibility degree is presented, which guarantees that the subscript value of an uncertain linguistic variable is subject to uniform distribution. To avoid the occurrence of such a situation that the uncertain linguistic hybrid geometric mean (ULHGM) operator might allocate counterproductive position weights to the data, its aggregation algorithm is improved, and the scheme selection method based on the improved ULHGM (IULHGM) operator is formulated. Finally, aiming at the maintainability design scheme selection of some equipment, the experts' evaluation data are aggregated by IULHGM operator and ULHGM operator respectively, which lead to different scheme ranking results, and the cause is analyzed. The case shows that the aggregation algorithm of the IULHGM operator is more accurate, reasonable and convenient than that of the ULHGM operator.