Abstract
In this paper, a novel method of ordering intuitionistic fuzzy numbers, combining the ‘value’ and the ‘ambiguity’ of an intuitionistic fuzzy number, is developed. The value and the ambiguity are calculated at \((\alpha , \beta )\)-levels, rather than calculating for the whole range of integration. These levels are termed as flexibility parameters, which allows a decision-maker to take a decision at levels of decision-making. In many studies, the reasonable properties of ranking intuitionistic fuzzy numbers were never tested. However, in this study, every effort is made to investigate the reasonable properties thoroughly. Furthermore, ordering of intuitionistic fuzzy numbers by existing methods relies heavily on intuition and the geometry of intuitionistic fuzzy numbers. The proposed method fully complies with the reasonable properties of ranking intuitionistic fuzzy numbers, as well as the coherent intuition and geometry of the intuitionistic fuzzy numbers. In addition, newer properties are being developed in this study. This demonstrates the novelty of the proposed method. A few numerical examples are also discussed demonstrating the proposed method. Lastly, the proposed method has been successfully applied to a risk analysis problem.

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Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96
Atanassov KT (1989) More on intuitionistic fuzzy sets. Fuzzy Sets Syst 33(1):37–45
Atanassov KT (1994) New operations defined over the intuitionistic fuzzy sets. Fuzzy Sets Syst 61(2):137–142
Atanassov KT (1999) Intuitionistic fuzzy sets. Intuitionistic fuzzy Sets. Springer, Heidelberg, pp 1–137
Atanassov KT (2000) Two theorems for intuitionistic fuzzy sets. Fuzzy Sets Syst 110(2):267–269
Bhattacharya K, De S (2020) Decision making under intuitionistic fuzzy metric distances. Ann Optim Theory Pract 3(2):49–64
Chakraborty D, Jana DK, Roy TK (2015) Arithmetic operations on generalized intuitionistic fuzzy number and its applications to transportation problem. OPSEARCH 52:431–471
Chen SM (1996) New methods for subjective mental workload assessment and fuzzy risk analysis. Cybern Syst 27(5):449–472
Chen S-J, Chen S-M (2008) Fuzzy risk analysis based on measures of similarity between interval-valued fuzzy numbers. Comput Math Appl 55(8):1670–1685
Chen S-M, Chen J-H (2009) Fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads. Expert Syst Appl, 36(3, Part 2):6833–6842
Chen SM, Munif A, Chen GS, Liu HC, Kuo BC (2012) Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. Expert Syst Appl 39(7):6320–6334
Chutia R (2017) Ranking of fuzzy numbers by using value and angle in the epsilon-deviation degree method. Appl Soft Comput 60:706–721
Chutia R (2021) Ranking interval type-2 fuzzy number based on a novel value-ambiguity ranking index and its application in risk analysis. Soft Comput 25(13):8177–8196
Chutia R (2021) Ranking of Z-numbers based on value and ambiguity at levels of decision making. Int J Intell Syst 36(1):313–331
Chutia R, Chutia B (2017) A new method of ranking parametric form of fuzzy numbers using value and ambiguity. Appl Soft Comput 52:1154–1168
Chutia R, Saikia S (2018) Ranking intuitionistic fuzzy numbers at levels of decision-making and its application. Expert Syst 35(5):e12292
Chutia R, Saikia S (2020) Ranking of interval type-2 fuzzy numbers using value and ambiguity. In: 2020 international conference on computational performance evaluation (ComPE). Shillong, India, pp 305–310
Darehmiraki M (2019) A novel parametric ranking method for intuitionistic fuzzy numbers. Iran J Fuzzy Syst 16(1):129–143
Das D, De P (2016) Ranking of intuitionistic fuzzy numbers by new distance measure. J Intell Fuzzy Syst 30(2):1099–1107
Das S, Guha D (2016) A centroid-based ranking method of trapezoidal intuitionistic fuzzy numbers and its application to MCDCM problems. Fuzzy Inf Eng 8(1):41–74
De SK (2018) Triangular dense fuzzy lock sets. Soft Comput 22(21):7243–7254
De SK (2020) On degree of fuzziness and fuzzy decision making. Cybern Syst 51(5):600–614
De SK, Beg I (2016) Triangular dense fuzzy sets and new defuzzification methods. J Intell Fuzzy Syst 31(1):469–477
De PK, Das D (2012) Ranking of trapezoidal intuitionistic fuzzy numbers. In: 2012 12th international conference on intelligent systems design and applications (ISDA), Kochi, India, pp 184–188
De SK, Mahata GC (2019) A comprehensive study of an economic order quantity model under fuzzy monsoon demand. Sadhana-Acad P Eng S, 44(4):1–12
Delgado M, Vila M, Voxman W (1998) On a canonical representation of fuzzy numbers. Fuzzy Sets Syst 93(1):125–135
Deli İ (2019) A novel defuzzification method of SV-trapezoidal neutrosophic numbers and multi-attribute decision making: a comparative analysis. Soft Comput 23(23):12529–12545
Deli I, Şubaş Y (2017) A ranking method of single valued neutrosophic numbers and its applications to multi-attribute decision making problems. Int J Mach Learn Cybern 8(4):1309–1322
Dubey D, Mehra A (2011) Linear programming with triangular intuitionistic fuzzy number. In: Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology. Atlantis Press, Aix-les-Bains, France, pp 563–569
Dubois D, Prade H (1980) Fuzzy sets and systems: theory and applications. Academic Press Inc, Orlando
Dutta P, Saikia B (2021) Arithmetic operations on normal semi elliptic intuitionistic fuzzy numbers and their application in decision-making. Granul Comput 6:163–179
Grzegorzewski P (2003) Distances and orderings in a family of intuitionistic fuzzy numbers. In: EUSFLAT conference, Zittau, Germany, pp 223–227
Jain R (1976) Decision making in the presence of fuzzy variables. IEEE Trans Syst Man Cybern Syst SMC-6(10):698–703
Jain R (1977) A procedure for multiple-aspect decision making using fuzzy sets. Int J Syst Sci 8(1):1–7
Kumar A, Kaur M (2013) A ranking approach for intuitionistic fuzzy numbers and its application. J Appl Res Technol 11(3):381–396
Li D-F (2008) A note on ”using intuitionistic fuzzy sets for fault-tree analysis on printed circuit board assembly. Microelectron Reliab 48(10):1741
Li D-F (2010) A ratio ranking method of triangular intuitionistic fuzzy numbers and its application to MADM problems. Comput Math Appl 60(6):1557–1570
Li D-F (2014) Decision and game theory in management with intuitionistic fuzzy sets, vol 308. Springer, Berlin
Li DF, Nan JX, Zhang MJ (2010) A ranking method of triangular intuitionistic fuzzy numbers and application to decision making. Int J Comput Intell Syst 3(5):522–530
Mitchell HB (2004) Ranking-intuitionistic fuzzy numbers. Int J Uncertain Fuzz 12(03):377–386
Mondal SP, Goswami A,Kumar De S (2019) Nonlinear triangular intuitionistic fuzzy number and its application in linear integral equation. Adv Fuzzy Syst
Nan J-X, Li D-F, Zhang M-J (2010) A lexicographic method for matrix games with payoffs of triangular intuitionistic fuzzy numbers. Int J Comput Intell Syst 3(3):280–289
Nayagam LGV, Jeevaraj S, Dhanasekaran P (2016) A linear ordering on the class of trapezoidal intuitionistic fuzzy numbers. Expert Syst Appl 60:269–279
Nayagam VLG, Jeevaraj S, Dhanasekaran P (2018) An improved ranking method for comparing trapezoidal intuitionistic fuzzy numbers and its applications to multicriteria decision making. Neural Comput Appl 30:671–682
Nehi HM (2010) A new ranking method for intuitionistic fuzzy numbers. Int J Fuzzy Syst 12(1):80–86
Rezvani S (2013) Ranking method of trapezoidal intuitionistic fuzzy numbers. Ann Fuzzy Math Inform 5(3):515–523
Salahshour S, Shekari G, Hakimzadeh A (2012) A novel approach for ranking triangular intuitionistic fuzzy numbers. AWER Procedia Inf Technol 1:442–446
Schmucke KJ (1984) Fuzzy sets: natural language computations, and risk analysis. University of Michigan Computer Science Press, Michigan
Seikh MR, Nayak PK, Pal M (2012) Generalized triangular fuzzy numbers in intuitionistic fuzzy environment. Int J Eng Res Dev 5(1):08–13
Uluçay V, Deli I, Şahin M (2019) Intuitionistic trapezoidal fuzzy multi-numbers and its application to multi-criteria decision-making problems. Complex Intell Syst 5(1):65–78
Wan S-P (2013) Multi-attribute decision making method based on possibility variance coefficient of triangular intuitionistic fuzzy numbers. Int J Uncertain Fuzz 21(02):223–243
Wan S-P, Li D-F (2013) Possibility mean and variance based method for multi-attribute decision making with triangular intuitionistic fuzzy numbers. J Intell Fuzzy Syst 24(4):743–754
Wang X, Kerre EE (2001) Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Sets Syst 118(3):375–385
Wang X, Kerre EE (2001) Reasonable properties for the ordering of fuzzy quantities (II). Fuzzy Sets Syst 118(3):387–405
Wang J, Zhang Z (2009) Multi-criteria decision-making method with incomplete certain information based on intuitionistic fuzzy number. Control Decis 24(2):226–230
Wei SH, Chen SM (2009) A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. Expert Syst Appl 36(1):589–598
Ye J (2011) Expected value method for intuitionistic trapezoidal fuzzy multicriteria decision-making problems. Expert Syst Appl 38(9):11730–11734
Zeng X-T, Li D-F, Yu G-F (2014) A value and ambiguity-based ranking method of trapezoidal intuitionistic fuzzy numbers and application to decision making. Sci World J
Zhang W-R (1986) Knowledge representation using linguistic fuzzy relations. University of South Carolina, Columbia
Zhang X, Xu Z (2012) A new method for ranking intuitionistic fuzzy values and its application in multi-attribute decision making. Fuzzy Optim Decis Mak 11(2):135–146
Zhu L-S, Xu R-N (2012) Fuzzy risks analysis based on similarity measures of generalized fuzzy numbers. Springer, Berlin, pp 569–587
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Chutia, R. A novel method of ranking intuitionistic fuzzy numbers using value and \(\theta \) multiple of ambiguity at flexibility parameters. Soft Comput 25, 13297–13314 (2021). https://doi.org/10.1007/s00500-021-06102-8
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DOI: https://doi.org/10.1007/s00500-021-06102-8