Rank aggregation based multi-attribute decision making with hybrid Z-information and its application

Abstract

Z-numbers contain both of the cognitive information and the reliability of information. Since there are many types of cognitive information, by considering the reliability of these information, decision making with hybrid Z-information would be a practical issue, which has merely been considered. The aim of this paper is to introduce a multi-attribute decision making (MADM) with hybrid Z-information based on ranking aggregation method. By using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, single rankings of alternatives under attributes are firstly produced. Then, final ranking(s) of alternatives with the lowest disagreement among single rankings could be derived according to ranking aggregation. As a result, a MADM with hybrid Z-information is transformed to be a ranking aggregation problem. The advantage of the developed method is that no algebra structures of hybrid Z-information is needed, so complex calculating process is avoided. In this paper, the mathematical structure of the case that MADM with hybrid Z-numbers is clear. Besides, the combination of ranking aggregation method and studies on Z-numbers could simplify the processing of hybrid Z-numbers. Finally, an example of supplier selection in green supply chain environment is introduced to illustrate the feasibility and validity of the developed model.