Confidence levels based Pythagorean fuzzy aggregation operators and its application to decision-making process

Computational and Mathematical Organization Theory

Volumn 23, Issue 4, 2017, Pages 546-571

  Garg, Harish ^a  

^a THAPAR UNIVERSITY   (India)

Author keywords

Aggregation operators; Confidence levels; Decision making; MCDM; Pythagorean fuzzy set

Indexed keywords

DECISION MAKING; FUZZY SETS; MATHEMATICAL OPERATORS;

AGGREGATION OPERATOR; CONFIDENCE LEVELS; DECISION MAKING PROCESS; FUZZY AGGREGATION OPERATORS; INTUITIONISTIC FUZZY SETS; ITS APPLICATIONS; MCDM; MULTI-CRITERIA DECISION MAKING METHODS;

MEMBERSHIP FUNCTIONS;

EID: 85011845621     PISSN: 1381298X     EISSN: 15729346     Source Type: Journal    
DOI: 10.1007/s10588-017-9242-8     Document Type: Article

References (32)

1. Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96
2. Dalman H (2016) Uncertain programming model for multi-item solid transportation problem. Int J Mach Learn Cybern 1–9. doi:10.1007/s13042-016-0538-7
3. Dalman H, Güzel N, Sivri M (2016) A fuzzy set-based approach to multi-objective multi-item solid transportation problem under uncertainty. Int J Fuzzy Syst 18(4):716–729
4. Garg H (2016a) Generalized intuitionistic fuzzy interactive geometric interaction operators using Einstein t-norm and t-conorm and their application to decision making. Comput Ind Eng 101:53–69
5. Garg H (2016b) Generalized intuitionistic fuzzy multiplicative interactive geometric operators and their application to multiple criteria decision making. Int J Mach Learn Cybern 7(6):1075–1092
6. Garg H (2016c) Generalized pythagorean fuzzy geometric aggregation operators using Einstein t-norm and t-conorm for multicriteria decision-making process. Int J Intell Syst. doi:10.1002/int.21860
7. Garg H (2016d) A new generalized improved score function of interval-valued intuitionistic fuzzy sets and applications in expert systems. Appl Soft Comput 38:988–999
8. Garg H (2016e) A new generalized pythagorean fuzzy information aggregation using Einstein operations and its application to decision making. Int J Intell Syst 31(9):886–920
9. Garg H (2016f) A novel accuracy function under interval-valued pythagorean fuzzy environment for solving multicriteria decision making problem. J Intell Fuzzy Syst 31(1):529–540
10. Garg H (2016g) A novel correlation coefficients between pythagorean fuzzy sets and its applications to decision-making processes. Int J Intell Syst 31(12):1234–1253
11. Garg H (2016h) Some series of intuitionistic fuzzy interactive averaging aggregation operators. SpringerPlus 5(1):999. doi:10.1186/s40064-016-2591-9
12. Garg H, Agarwal N, Tripathi A (2015) Entropy based multi-criteria decision making method under fuzzy environment and unknown attribute weights. Glob J Technol Optim 6:13–20
13. Kumar K, Garg H (2016) TOPSIS method based on the connection number of set pair analysis under interval-valued intuitionistic fuzzy set environment. Comput Appl Math 1–11. doi:10.1007/s40314-016-0402-0
14. Nancy Garg H (2016a) An improved score function for ranking neutrosophic sets and its application to decision-making process. Int J Uncertain Quantif 6(5):377–385
15. Nancy Garg H (2016b) Novel single-valued neutrosophic decision making operators under frank norm operations and its application. Int J Uncertain Quantif 6(4):361–375
16. Peng X, Yang Y (2015) Some results for pythagorean fuzzy sets. Int J Intell Syst 30(11):1133–1160
17. Wang W, Liu X (2012) Intuitionistic fuzzy information aggregation using Einstein operations. IEEE Trans Fuzzy Syst 20(5):923–938
18. Xu Y, Wang H, Merigo JM (2014) Intuitionistic fuzzy einstein choquet intergral operators for multiple attribute decision making. Technol Econ Dev Econ 20(2):227–253
19. Xu Z, Zhao N (2016) Information fusion for intuitionistic fuzzy decision making: an overview. Inf Fusion 28:10–23
20. Xu ZS (2007) Intuitionistic fuzzy aggregation operators. IEEE Trans Fuzzy Syst 15:1179–1187
21. Xu ZS, Yager RR (2006) Some geometric aggregation operators based on intuitionistic fuzzy sets. Int J Gen Syst 35:417–433
22. Yager RR (1988) On ordered weighted avergaing aggregation operators in multi-criteria decision making. IEEE Trans Syst Man Cybern 18(1):183–190
23. Yager RR (2013) Pythagorean fuzzy subsets. In Procedding Joint IFSA World Congress and NAFIPS Annual Meeting. Edmonton, Canada, pp 57–61
24. Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22:958–965
25. Yager RR, Abbasov AM (2013) Pythagorean membeship grades, complex numbers and decision making. Int J Intell Syst 28:436–452
26. Yager RR, Kacprzyk J (1997) The ordered weighted averaging operators: theory and applications. Kluwer Acadenmic Publisher, Boston
27. Ye J (2007) Improved method of multi criteria fuzzy decision making based on vague sets. Comput Aided Des 39(2):164–169
28. Ye J (2009) Multicriteria fuzzy decision-making method based on a novel accuracy function under interval-valued intuitionistic fuzzy environment. Expert Syst Appl 36:6809–6902
29. Yu D (2014) Intuitionistic fuzzy information aggregation under confidence levels. Appl Soft Comput 19:147–160
30. Yu D (2015) A scientometrics review on aggregation operator research. Scientometrics 105(1):115–133
31. Yu D, Shi S (2015) Researching the development of atanassov intuitionistic fuzzy set: using a citation network analysis. Appl Soft Comput 32:189–198
32. Zhang XL, Xu ZS (2014) Extension of TOPSIS to multi-criteria decision making with pythagorean fuzzy sets. Int J Intell Syst 29:1061–1078