Multi-criteria decision-making method based on intuitionistic normal fuzzy aggregation operators

Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice

Volumn 33, Issue 6, 2013, Pages 1501-1508

  Wang, Jian Qiang ^a   Li, Kang Jian ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Intuitionistic normal fuzzy aggregation operators; Intuitionistic normal fuzzy numbers; Multi criteria decision making

Indexed keywords

ARITHMETIC AVERAGING; AVERAGING OPERATORS; COMPREHENSIVE EVALUATION; FUZZY AGGREGATION OPERATORS; MULTI-CRITERIA DECISION MAKING; MULTI-CRITERIA DECISION-MAKING METHODS; MULTIPLE CRITERIA DECISION-MAKING PROBLEMS; NORMAL FUZZY NUMBER;

DECISION MAKING; FUZZY RULES;

MATHEMATICAL OPERATORS;

EID: 84880392967     PISSN: 10006788     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (27)

1. Atanassov K. Intuitionistic fuzzy sets [J]. Fuzzy Sets and Systems, 1986, 20: 87-96.
2. Atanassov K, Gargov G. Interval-valued intuitionistic fuzzy sets [J]. Fuzzy Sets and Systems, 1989, 31(3): 343-349
3. Liu F, Yuan X H. Fuzzy number intuitionistic fuzzy set [J]. Fuzzy Systems and Mathematics, 2007, 21(1): 88-91.
4. Wang J Q. Multi-criteria interval intuitionistic fuzzy decision-making approach with incomplete certain information [J]. Control and Decision, 2006, 21(11): 1253-1256
5. Dai Y Q, Xu Z S, Da Q L. Approach to multiple attribute decision making based on different intuitionistic preference structures [J]. Journal of Southeast University: Nature Science Edition, 2007, 37(4): 706-710
6. Boran F E, Genc S, Kurt M, et al. A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method [J]. Expert Systems with Applications, 2009, 36: 11363-11368.
7. Li D F. Multiattribute decision making method based on generalized OWA operators with intuitionistic fuzzy sets [J]. Expert Systems with Applications, 2010, 37: 8673-8678.
8. Xu Z S. Choquet integrals of weighted intuitionistic fuzzy information [J]. Information Sciences, 2010, 180: 726-736.
9. Park J H, Cho H J, Hwang J S, et al. Extension of the VIKOR method to dynamic intuitionistic fuzzy multiple attribute decision making [J]. Third International Workshop on Advanced Computational Intelligence, 2010: 189-195.
10. Feng X Q, Qian G. The method of grey related analysis to multiple attribute decision making problems with intuitionistic fuzzy sets [J]. International Conference on E-Business and E-Government, 2010: 1588-1591.
11. 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 [J]. Expert Systems with Applications, 2011, 38: 7647-7658.
12. Tan C Q. A multi-criteria interval-valued intuitionistic fuzzy group decision making with Choquet integral-based TOPSIS [J]. Expert Systems with Applications, 2011, 38: 3023-3033.
13. Ye J. Fuzzy cross entropy of interval-valued intuitionistic fuzzy sets and its optimal decision-making method based on the weights of alternatives [J]. Expert Systems with Applications, 2011, 38: 6179-6183.
14. Shu M H, Cheng C H, Chang J R. Using intuitionistic fuzzy sets for fault-tree analysis on printed circuit board assembly [J]. Microelectronics Reliability, 2006, 46(12): 2139-2148.
15. Wang J Q. Overview on fuzzy multi-criteria decision-making approach [J]. Control and Decision, 2008, 23(6): 601-606.
16. Wang J Q, Li H B. Multi-criteria decision-making method based on aggregation operators for intuitionistic linguistic fuzzy numbers [J]. Control and Decision, 2010, 25(10): 1571-1574.
17. Wang J Q, Zhang Z. Aggregation operators on intuitionistic trapezoidal fuzzy number and its application to multi-criteria decision making problems [J]. Journal of Systems Engineering and Electronics, 2009, 20(2): 321-326.
18. Wang J Q, Zhang Z. Multi-criteria decision-making method with incomplete certain information based on intuitionistic fuzzy number [J]. Control and Decision, 2009, 24(2): 226-230.
19. Wan S P, Dong J Y. Method of intuitionistic trapezoidal fuzzy number for multi-attribute group decision [J]. Control and Decision, 2010, 25(5): 773-776.
20. Wang J Q, Nie R R. Multi-criteria group decision-making method based on intuitionistic trapezoidal fuzzy information [J]. Systems Engineering - Theory & Practice, 2012, 32(8): 1747-1753.
21. Mahapatra B S, Mahapatra G S. Intuitionistic fuzzy fault tree analysis using intuitionistic fuzzy numbers [J]. International Mathematical Forum, 2010, 5: 1015-1024.
22. Li D F. A ratio ranking method of triangular intuitionistic fuzzy numbers and its application to MADM problems [J]. Computers & Mathematics with Applications, 2010, 60: 1557-1570.
23. Wang J Q, Nie R R. Interdependent multi-criteria intuitionistic fuzzy decision-making approach [J]. Control and Decision, 2011, 26(9): 1348-1352.
24. Wan S P. Survey on intuitionistic fuzzy multi-attribute decision making approach [J]. Control and Decision, 2010, 25(11): 1601-1606.
25. Yang M S, Ko C H. On a class of fuzzy c-numbers clustering procedures for fuzzy data [J]. Fuzzy Sets and Systems, 1996, 84: 49-60.
26. Li D Y, Liu C Y. Study on the universality of the normal cloud model [J]. Engineering Science, 2004, 6(8): 28-34.
27. Xu R N, Li C L. Regression prediction for fuzzy time series [J]. Applied Mathematics A Journal of Chinese Universities (Series A), 2001, 16(4): 451-461.