Extended TODIM method based on VIKOR for q‐rung orthopair fuzzy information measures and their application in MAGDM problem of medical consumption products

Abstract

Nowadays, supply chain management (SCM) has achieved considerable attention from all over the world. q-rung orthopair fuzzy set, developed by Yager, is the entirety of the most prominent tool to express fuzzy data in the decision-making problems. In this study, the introduction of two new generalised measures (entropy and Jensen–Tsalli divergence measure) of q-rung orthopair fuzzy information involving one real parameter is given. The proposed measures have satisfied all the necessary mathematical properties of being a measure. Then the introduced entropy and divergence measure is used to obtain the objective weights. Based on the proposed entropy and divergence measure, we proposed a new decision method to deal with multiple-attribute group decision-making problems under the q-rung orthopair fuzzy environment. Then, on the basis of the TODIM and VIKOR techniques, an integrated TODIM-VIKOR approach is developed to solve multiattribute group decision-making problem. In this paper, TODIM aims to determine the overall dominance degree and VIKOR aims to determine the compromise solution. Lastly, we handle a supplier selection problem to verify the performance of the proposed q-rung orthopair fuzzy TODIM-VIKOR method and results explore the reliability and effectiveness of our proposed methodology by comparing the ranking solution with the ranking results of the existing approaches.