An improvement decision-making method by similarity and belief function theory

This study considers a new aspect of the belief function theory to define a belief set, which is characterized by truth, uncertainty and falsity belief degrees as a 3D vector representation. Then, based on the implication of a belief set, one of the similarity measures (i.e. Cosine, Jaccard and Dice) between two belief sets is defined. Furthermore, the weighted similarity measure of these different species between each alternative and ideal alternative is presented to rank alternatives and determine the best one. Finally, a comparison between similarity measures and an application of a new method based on similarity measures between two belief sets in the decision-making process is calculated to show the capability and validity of the proposed method.

Automated summary

This study introduces a new approach in the belief function theory to define belief sets and defines a similarity measure between two belief sets. The weighted similarity measure is used to rank and determine the best alternative. The application of this method in the decision-making process demonstrates its capability and validity.