A novel defuzzifying approach to car evaluation and selection under fuzzy environment
This paper proposes a new method for ranking fuzzy numbers by difference between relative areas. Comparative examples illustrate the advantage of the proposed method. The ranking method is further applied to help establish a defuzzified multiple level FMADM model, which avoids the complicated aggregation of fuzzy numbers so that the multiple level FMADM problem can be efficiently solved. A numerical example of car evaluation and selection illustrates the feasibility of the proposed model.
car evaluation and selection ranking relative areas multiple level fmadm