An improved q-rung orthopair fuzzy set with partial weight information and application based on inferior ratio method

Sunit Kumar () and Satish Kumar ()
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Sunit Kumar: Chandigarh University
Satish Kumar: Chandigarh University

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 5, No 21, 2404-2412

Abstract: Abstract Yager has introduced the q-rung orthopair fuzzy set (q-ROFS), which is the most significant generalization of the Pythagorean fuzzy set (PFS). The q-rung orthopair adjusts in the needed boundary range when the q rung value increases. As a result, the q-ROFS input range is more adaptable, resilient, and appropriate than the intuitionistic fuzzy set and PFS. In this paper, we proposed new entropy measure for q-rung orthopair fuzzy set and it is being proved that the proposed entropy measure follows all the requirements of an entropy measure for q-ROFs. Numerical example depicts the efficiency of the proposed entropy measure. Furthermore, in the present paper entropy weighted method is applied to compute weights vector where partial information is used for criteria weights. Then, a new decision-making method using inferior ratio method based on proposed entropy measure is put forward. The working of the proposed multi-criteria decision-making model is explained through a numerical example. At last, a detailed comparison of the proposed model with certain current approaches is given, which demonstrates that the proposed decision model is more effective and beneficial than existing methodologies.

Keywords: TODIM; Inferior ratio; q-Rung orthopair fuzzy set; 94A15; 94A24; 26D15 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-022-01651-z

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