TOPSIS-Based MAGDM Under Linguistic Z Number Information

This chapter deals with solving multiple attribute group decision-making (MAGDM)problems based on TOPSIS under linguistic Z number (LZN)-based on uncertain information. The LZN is an ordered pair, where the second component describes how sure we are that the first component is. Thus, the decision information is more powerful than the existing one. In the proposed method, the weight of experts and attributes are unknown. First, we proposed an expert risk parameter-based weight determination technique. Then, we aggregate the experts’ decision information with expert weights. After that, we derived the weight of attributes from the aggregate decision matrix by the entropy method. Finally, we rank the objects concerning the closeness index by measuring the distance between the aggregate decision matrix to the LZN positive ideal solution (LZNPIS) and the distance between the aggregate decision matrix to the LZN negative ideal solution (LZNNIS). The chapter demonstrates the use of the method with the optimal selection of suppliers for products of new machinery in the agricultural industry. The numerical result of this chapter indicates that the method is simple, effective, and easily applicable. This method is also applicable in other MAGDM problems for optimal selection of alternatives.