An evidential reasoning based approach for GDM with uncertain preference ordinals

The group-ranking problem is ubiquitous in the real life, which is a group decision-making (GDM) problem and cannot be completed independently by individuals. However, different experts or decision-makers (DMs) may provide their preference information on alternatives in the form of uncertain preference ordinals. This paper developed an evidential reasoning (ER) based method to deal with various types of preference information on alternatives such as precise and imprecise, complete and incomplete, and known and unknown, which may provide by experts or DMs in the process of alternatives ranking. The proposed method allows experts or DMs to express their preferences independently and freely using belief structure, and provides a means based on evidence distance to determine the relative weights of belief structures, which is not need to solve the complex optimization model. Furthermore, the interval ER algorithm is employed to aggregate different types of preference information with a rigorous and systematic framework. The feasibility and rationality of the method are explained and verified by examples.