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.
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References
Akram M, Muzzamal S (2021) Decision-making with q-rung orthopair fuzzy graph structures. Granular Comput. https://doi.org/10.1007/s41066-021-00281-3
Arya V, Kumar S (2020) Multi-criteria decision making problem for evaluating ERP System using entropy weighting approach and q-rung orthopair fuzzy TODIM approach. Granular Comput 6(4):977–989
Arya V, Kumar S (2021a) A novel VIKOR-TODIM approach based on Havrda-Charvat-Tsallis Entropy of Intuitionistic fuzzy sets to evaluate Management Information System. Fuzzy Inf Eng. https://doi.org/10.1080/16168658.2020.1840317
Arya V, Kumar S (2021b) Extended TODIM method based on VIKOR for q-rung orthopair fuzzy information measures and their application in MAGDM problem of medical consumption products. Int J Intell Syst 36(11):6837–6870. https://doi.org/10.1002/int.22571
Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96
Chen SM, Chang CH (2015) A novel similarity measures between Attansov’s intuitionistic fuzzy sets based on transformation techniques with application to pattern recognition. Inf Sci 291:96–114
Chen SM, Cheng SH, Lan TC (2016) Multicriteria decision making bed on TOPSIS method and similarity measures between intuitionistic fuzzy values. Inf Sci 367:279–295
Garg H, Chen SM (2020) Multiattribute group decision making based on neutrality aggregation operators of q-rung orthopair fuzzy sets. Inf Sci 517:427–447
Hasseb A, Singh S (2021) An innovative picture fuzzy distance measure and novel multi-attribute decision-making method. Complex Intell Syst 7:781–805
Huang G, Liu Y (2005) The fuzzy entropy of vague sets based on non- fuzzy sets. Comput Appl Softw 22(6):16–17
Khan MJ, Kumam P, Shutaywi M, Kumam W (2021) Improved knowledge measures for q-rung orthopair fuzzy sets. Int J Comput Intell Syst 14(1):1700–1713
Kumar S, Kumar S (2020) A generalization of Gini Simpson Index under fuzzy environment. Adv Math Sci J 9(8):5443–5454
Kumar S, Kumar S (2021) Multi-attribute decision-making problem based on TODIM with Gini Simpson index of diversity for intuitionistic fuzzy sets. Adv Intell Syst Comput. https://doi.org/10.1007/978-981-16-5207-3_63
Liang X, Wei C, Xia M (2013) New entropy, similarity measure of intuitionistic fuzzy sets and their applications in group decision making. Int J Comput Intell Syst 26(5):987–1001
Liu P, Liu J (2018) Some q-rung orthopair fuzzy Bonferrono mean operators and their application to multi-attribute group decision making. Int J Intell Syst 33(2):315–347
Liu P, Wang P (2018) Some q-Rung orthopair fuzzy aggregation operators and their applications to multi-attribute decision making. Int J Intell Syst 33(2):259–280
Liu P, Wang P (2019) Multiple-attribute decision-making based on Archimedean Bonferroni operators of q-rung orthopair fuzzy numbers. IEEE Trans Fuzzy Syst 27(5):834–843
Liu P, You X (2017) Probabilistic linguistic TODIM approach for multiple attribute decision-making. Granular Comput 2(4):333–342
Liu P, Wang P, Zhu B (2015) An extended multiple attribute group decision making method based on q-rung orthopair fuzzy numbers. IEEE Access 99:1–1
Peng X, Dai J (2019) Research on the assessment of classroom teaching quality with q-rung orthopair fuzzy information based on multiparametric similarity measure and combinative distance-based assessment. Int J Intell Syst 34(7):1588–1630
Verma R (2020) Multiple attribute group decision making based on order-α divergence and entropy measures under q-rung orthopair fuzzy environment. Int J Intell Syst 35(4):718–750
Vlachos IK, Sergiadis GD (2015) Intuitionistic fuzzy information: applications to pattern recognition. Pattern Recogn Lett 28(2):197–206
Xu Z, Wu J (2010) Intuitionistic fuzzy C-means clustering algorithms. J Syst Eng Electron 21(4):580–590
Yager RR (2017) Generalized orthopair fuzzy sets. IEEE Trans Fuzzy Syst 25(5):122–1230
Yager RR, Abbasov AM (2013) Pythagorean membership grades, complex numbers and decision making. Int J Intell Syst 28(05):436–452
Yang W, Pang Y (2019) New q-rung orthopair fuzzy partitioned Bonferroni mean operators and their application in multi-attribute decision making. Int J Intell Syst 34(3):439–476
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353
Zeng S, Chen SM, Kuo LW (2019) Multi-attribute decision making based on novel score function of intuitionistic fuzzy values and modified VIKOR method. Inf Sci 488:76–92
Zhang QS, Jiang SY (2008) A note on information entropy measures for vague sets and its applications. Inf Sci 178(21):4184–4191
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Kumar, S., Kumar, S. An improved q-rung orthopair fuzzy set with partial weight information and application based on inferior ratio method. Int J Syst Assur Eng Manag 13, 2404–2412 (2022). https://doi.org/10.1007/s13198-022-01651-z
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DOI: https://doi.org/10.1007/s13198-022-01651-z