New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS

Abstract

A new multiple attribute decision making method based on the q-rung orthopair hesitant fuzzy sets has been developed. The evaluation values are given as q-rung orthopair hesitant fuzzy values. Then some weighted similarity functions are defined. A linear programming model is proposed to derive attribute weights based on the similarity functions for the case of partly known attribute weight information and a formula is given to determine attribute weight based on similarity function and the Lagrange function for completely unknown attribute weights. Finally, TOPSIS method is used to rank alternatives. The application of the proposed approach is explored by the application of purchase self-service book sterilizer problem. Some comparisons are also conducted to demonstrate advantages of the proposed method.