An Integrated Two-Dimension Linguistic Intuitionistic Fuzzy Decision-Making Approach for Unmanned Aerial Vehicle Supplier Selection

With the rapid development of unmanned aerial vehicles (UAVs) and their applications in problems such as power line inspection, selecting the appropriate UAV supplier according to several sustainable attributes has attracted many interests. In this regard, an integrated multiattribute group decision-making (MAGDM) method based on the best-worst method (BWM) and MULTIMOORA method with two-dimension linguistic intuitionistic fuzzy variables (2DLIFVs) is proposed in this paper for the selection of UAV suppliers. First, the 2DLIFV is utilized to represent the uncertain, fuzzy, and linguistic evaluations of the experts on the evaluation attributes. Second, the two-dimension linguistic intuitionistic fuzzy BWM (2DLIF-BWM) is introduced to compute the weights of the attributes. Then, a novel expert weight calculation method that combines the uncertainty degree and consensus degree of the experts is introduced. Next, the 2DLIF-MULTIMOORA method is proposed, where the aggregation operators and distance measures of the 2DLIFVs are used to determine the ranking results of different alternatives. Finally, a real case of selecting a sustainable UAV supplier for power line inspection is presented to illustrate the process of the proposed method. The experimental results are further analyzed through sensitivity and comparative analyses to show the feasibility and effectiveness of the proposed method. From the results, it can be found that the proposed method can more flexibly represent the uncertain assessments while providing reasonable and reliable results.