#5774. Extended TODIM method based on VIKOR for q-rung orthopair fuzzy information measures and their application in MAGDM problem of medical consumption products

July 2026publication date
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Theoretical Computer Science;
Human-Computer Interaction;
Artificial Intelligence;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
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.
Keywords:
divergence measure; entropy; MAGDM; q-rung orthopair fuzzy number

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