A probabilistic and decision attitude aggregation operator for intuitionistic fuzzy environment

International Journal of Intelligent Systems

Volumn 28, Issue 8, 2013, Pages 806-839

  Agarwal, Manish ^a   Hanmandlu, Madasu ^a   Biswas, Kanad K ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATION OPERATOR; DECISION ATTITUDES; DECISION MAKERS; FUZZY MEMBERSHIP; HUMAN EXPERT; IMPRECISE PROBABILITIES; INTUITIONISTIC FUZZY; UNCERTAIN INFORMATIONS;

ARTIFICIAL INTELLIGENCE; SOFTWARE ENGINEERING;

FUZZY SETS;

EID: 84879237406     PISSN: 08848173     EISSN: 1098111X     Source Type: Journal    
DOI: 10.1002/int.21603     Document Type: Article

References (62)

1. Atanassov K., Intuitionistic fuzzy sets. Fuzzy Sets Syst 1986; 20: 87-96.
2. Cornelis C, Deschrijver G, Kerre E,. Implication in intuitionistic fuzzy and interval-valued fuzzy set theory: construction, classification, application. Int J Approx Reason 2004; 35: 55-95.
3. Denoeux T,. Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence. Artif Intell 2008; 172: 234-264.
4. Deschrijver G, Cornelis C, Kerre E,. On the representation of intuitionistic fuzzy t-norms and t-conorms. IEEE Trans Fuzzy Syst 2004; 12 (1): 45-61.
5. Deschrijver G, Kerre EE,. On the position of intuitionistic fuzzy set theory in the framework of theories modelling imprecision. Inform Sci 2007; 177: 1860-1866.
6. Dimova L, Sevastianov P, Sevastianov D,. MCDM in a fuzzy setting: investment projects assessment application. Int J Prod Econ 2006; 100: 10-29.
7. Dubois D, Gottwald S, Hajek P, Kacprzyk J, Prade H,. Terminological difficulties in fuzzy set theory-the case of intuitionistic fuzzy sets. Fuzzy Sets Syst 2005; 156: 485-491.
8. Gau WL, Buehrer DJ,. Vague sets. IEEE Trans Syst Man Cybern 1993; 23: 610-614.
9. Grzegorzewski P, Mrowka E,. Some notes on (Atanassov's) intuitionistic fuzzy sets. Fuzzy Sets Syst 2005; 156: 492-495.
10. Li D.-F., Multiattribute decision making models and methods using intuitionistic fuzzy sets. J Comput Syst Sci 2005; 70: 73-85.
11. Lin L, Yuan X-H, Xia Z-Q,. Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets. J Comput Syst Sci 2007; 73: 84-88.
12. Liu H-W, Wang G-J,. Multi-criteria decision-making methods based on intuitionistic fuzzy sets. Eur J Oper Res 2007; 179: 220-233.
13. Atanassov K, Pasi G, Yager R, Atanassova V,. Intuitionistic fuzzy group interpretations of multi-person multi-criteria decision making. In: Proc Third Conf of the European Society for Fuzzy Logic and Technology, EUSFLAT'2003, Zittau, September 10-12, 2003; pp 177-182.
14. Pasi G, Yager Y, Atanassov K,. Intuitionistic fuzzy graph interpretations of multi-person multi-criteria decision making: Generalized net approach. In: Proc. 2004 Second Int IEEE Conf Intelligent Systems; 2004. pp 434-439.
15. Chen T-Y, Wang H-P, Lu Y-Y,. A multicriteria group decision-making approach based on interval-valued intuitionistic fuzzy sets: A comparative perspective. Expert Syst Appl 2011; 38 (6): 7647-7658.
16. Boran FE, Genç S, Kurt M, Akay D,. A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Syst Appl 2009; 36 (8): 11363-11368.
17. Chen Z, Yang W,. A new multiple attribute group decision making method in intuitionistic fuzzy setting. Appl Math Model 2011; 35 (9): 4424-4437.
18. Xu Z,. A method based on distance measure for interval-valued intuitionistic fuzzy group decision making. Inform Sci 2010; 180 (1): 181-190.
19. Li Dengfeng, Cheng Chuntian, New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions. Pattern Recognition Letters 2002; 23 (1-3): 221-225.
20. Abbas SE, On intuitionistic fuzzy compactness. Inform Sci 2005; 173: 75-91.
21. Davvaz B, Dudek WA, Jun YB,. Intuitionistic fuzzy Hv-submodules. Inform Sci 2006; 176: 285-300.
22. Xu ZS,. Models for multiple attribute decision-making with intuitionistic fuzzy information. Int J Uncertainty Fuzziness Knowl-Based Syst 2007; 15 (3): 285-297.
23. Xu ZS,. Intuitionistic preference relations and their application in group decision making. Inform Sci 2007; 177 (11): 2363-2379.
24. Xu ZS,. Intuitionistic fuzzy aggregation operators, IEEE Trans Fuzzy Syst 2007; 15 (6): 1179-1187.
25. Xu ZS, Yager RR,. Some geometric aggregation operators based on intuitionistic fuzzy sets. Int J Gen Syst 2006; 35: 417-433.
26. Xu Z, Yager RR,. Dynamic intuitionistic fuzzy multi-attribute decision making, Int J Approx Reason 2008; 48 (1): 246-262.
27. Merigõ JM,. Fuzzy multi-person decision making with fuzzy probabilistic aggregation operators. Int J Fuzzy Systems 2011; 13 (3): 163-174.
28. Merigõ JM, Wei GW,. Probabilistic aggregation operators and their application in uncertain multi-person decision making. Technol Econ Devel Econ 2011; 17 (2): 335-351.
29. Merigõ JM,. The probabilistic weighted average and its application in multi-person decision making. Int J Intelligent Syst 2012; 27 (5): 457-476.
30. Merigõ JM, Casanovas M, Engemann KJ,. Group decision making with generalized and probabilistic aggregation operators. Int J Innovative Comput Inform Control 2012; 8 (7A): 4823-4835.
31. Yager RR, Filev DP,. Induced ordered weighted averaging operators. IEEE Trans Syst Man Cybern B 1999; 29: 141-150.
32. Yager RR,. Generalized OWA aggregation operators. Fuzzy Optim Decision Making 2004; 3: 93-107.
33. Yager RR,. Using trapezoids for representing granular objects: Applications to learning and OWA aggregation. Inform Sci 2008; 178 (2): 363-380.
34. Wei GW,. Induced intuitionistic fuzzy ordered weighted averaging operator and its application to multiple attribute group decision making. Lect Notes Comput Sci 2008; 5009: 124-131.
35. Merigõ JM,. Probabilities with OWA operators. Expert Syst Appl 2012; 39 (13): 11456-11467.
36. Yager RR, Engemann KJ, Filev DP,. On the concept of immediate probabilities. Int J Intell Syst 1995; 10 (4): 373-397.
37. Engemann KJ, Filev DP, Yager RR,. Modelling decision making using immediate probabilities. Int J Gen Syst 1996; 24 (3): 281-294.
38. Merigõ JM,. Fuzzy decision making using immediate probabilities. Comput Ind Eng 2010; 58 (4): 651-657.
39. Wallsten TS, Budescu DV, Rapoport A, Zwick R, Forsyth B,. Measuring the vague meanings of probability terms. J Exp Psychol: Gen 115 (4), 348-365, 1986.
40. Zadeh LA,. Fuzzy probabilities. Inform Process Manag 1984; 20: 363-372.
41. Zadeh LA,. The concept of a linguistic variable and its application to approximate reasoning. Part 1, 2 and 3. Inform Sci 1975; 8: 199-249, 301-357; 9 (1976) 43-80.
42. Halliwell J,. Linguistic probability theory, PhD Thesis, School of Informatics, University of Edinburgh, Edinburgh, UK; 2007.
43. Shanteau J,. What does it mean when experts disagree ? In, Salas E., Klein G. A., editors. Linking expertise and naturalistic decision making. Florence, KY: Psychology Press; 2001. pp 229-244.
44. Shanteau J, Weiss DJ, Thomas RP, Pounds JC,. Performance-based assessment of expertise: how to decide if someone is an expert or not. Eur J Oper Res 2002; 136 (2): 253-263.
45. Hwang CL, Yoon K,. Multiple attributes decision making methods and applications, Berlin, Germany: Springer; 1981.
46. Yager RR,. Generalizing variance to allow the inclusion of decision attitude in decision making under uncertainty. Int J Approx Reason 2006; 42 (3): 137-158.
47. Yager RR,. Including decision attitude in probabilistic decision making. Int J Approx Reason 1999; 21 (1): 1-21.
48. Yager RR,. Fuzzy modeling for intelligent decision making under uncertainty. IEEE Trans Syst Man Cybern B 2000; 30 (1): 60-70.
49. Yager RR., On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Trans Syst Man Cybern 1988; 18 (1): 183-190.
50. Torra V., OWA operators in data modeling and reidentification. IEEE Trans Fuzzy Syst 2004; 12 (5): 652-660.
51. Yager RR., Fuzzy aggregation of modular neural networks with ordered weighted averaging operators. Int J Approx Reason 1995; 13: 359-375.
52. Merigõ JM, Gil-Lafuente AM,. The induced generalized OWA operator. Inform Sci 2009; 179 (6): 729-741.
53. Zhou L-G, Chen H-Y, Merigõ JM, Gil-Lafuente AM,. Uncertain generalized aggregation operators. Expert Syst Appl 2012; 39 (1): 1105-1117.
54. Zhou L, Chen H, Liu J,. Generalized power aggregation operators and their applications in group decision making. Comput Ind Eng. Available online December 31, 2011.
55. Li D-F., The GOWA operator based approach to multiattribute decision making using intuitionistic fuzzy sets. Math Comput Model 2011; 53 (5-6): 1182-1196.
56. Yager RR,. On generalized measures of realization in uncertain environments. Theory Decision 1992; 33: 41-69.
57. Wu Z, Chen Y,. The maximizing deviation method for group multiple attribute decision making under linguistic environment. Fuzzy Sets Syst 2007; 158 (14): 1608-1617.
58. Herrera F, Herrera-Viedma E,. Linguistic decision analysis: steps for solving decision problems under linguistic information, Fuzzy Sets Syst 2000; 115: 67-82.
59. Xu ZS, Da QL,. The uncertain OWA operator. Int J Fuzzy Intell Syst 2002; 17: 569-575.
60. Xu ZS,. An overview of methods for determining OWA weights. Int J Intell Syst 2005; 20: 843-865.
61. Xu Z, Xia M,. Induced generalized intuitionistic fuzzy operators. Knowledge Based Systems 2011; 24 (2): 197-209.
62. Chen SM, Tan JM,. Handling multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets Syst 1994; 67: 163-172.