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A cubic q-rung orthopair fuzzy TODIM method based on Minkowski-type distance measures and entropy weight

  • Soft computing in decision making and in modeling in economics
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Abstract

The main aim of the present study is to develop a novel TODIM method under cubic q-rung orthopair fuzzy environment, where information about the weights of both decision makers (DMs) and criteria is fully unknown. First, we introduce some novel operations along with their relevant properties. Afterward, we propose a Minkowski-type distance measure for cubic q-rung orthopair fuzzy sets (Cq-ROFSs). We list some properties of the proposed distance measures and some special cases about various parameter values. Next, the entropy measure between two Cq-ROFSs is disclosed, and part of the proposed entropy measure characteristics is presented. Further, this study put forward the method for finding the weights of DMs and criteria. In the developed method, firstly, weights of DMs are obtained using the proposed distance measure and cubic q-rung orthopair fuzzy weighted averaging operator. Then, the weights of criteria are determined by the developed entropy measure. A novel TODIM method is developed utilizing the proposed Minkowski-type distance measures for ranking alternatives in light of the acquired criteria weights. To demonstrate the applicability and validity of the presented work, we address the talent recruitment problem. Moreover, we discuss the influence of parameters on decision-making results. Finally, a comparative study with existing work is made.

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Ali, J., Bashir, Z. & Rashid, T. A cubic q-rung orthopair fuzzy TODIM method based on Minkowski-type distance measures and entropy weight. Soft Comput 27, 15199–15223 (2023). https://doi.org/10.1007/s00500-023-08552-8

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