Consistency-based decision-making method with linguistic Q-rung orthopair fuzzy preference relation for power battery selection of new energy vehicles

Abstract

In the era of global petrochemical depletion and increasingly serious environmental pollution, new energy vehicles, as a key industry to build a sustainable low-carbon society, have been paid more and more attention by countries all over the world. As the “heart” of new energy vehicles, power battery plays an important role in the core competitiveness of enterprises. Aiming at the fuzziness and uncertainty of complex power battery selection, a two-stage consistency optimization model based on preference relations and an interactive consistency improvement process are established in this paper. Firstly, by considering the interaction between membership and non-membership, this paper proposes an improved linguistic q-rung orthopair fuzzy weighted averaging operator. Then, the concept of linguistic q-rung orthopair fuzzy preference relation (Lq-ROFPR) is proposed, and its additive consistency index is given based on linguistic scaling function. Whereafter, for the Lq-ROFPR with unacceptable consistency, an interactive mechanism is proposed to improve the consistency level, which considers the minimum adjustment size of preference modification and the minimum number of adjustment elements in turn. Moreover, the method for solving the multi-attribute decision-making problems is formed and applied to the selection of power batteries in XP automobile company. Finally, the simulation experiment and comparative analysis with other methods show the effectiveness and rationality of this method in consistency optimization.