A hierarchical multi-criteria group decision-making method based on TOPSIS and hesitant fuzzy information

Abstract

This study develops a novel approach based on the technique for order performance with similarity to ideal solution (TOPSIS), to solve the multi-criteria group decision-making problem using hesitant fuzzy information. Firstly, some basic concepts about the hesitant fuzzy sets are described. Then, the proposed hesitant fuzzy hierarchical TOPSIS method is elaborated. In this method, we consider the weight of each decision maker to decrease the errors. Also, decision makers could assign their preferences' values to compute the separation measure obtained from the concept of weight of the strategy of 'the majority of criteria' in the classic VIKOR method. Finally, a numerical example from the literature about the selection of new product idea from a real case study is presented to indicate the usefulness and performance of the proposed hesitant fuzzy hierarchical TOPSIS method. Comparative analysis is also provided to show the superiority of the proposed method against the fuzzy VIKOR method.