Please wait a minute...
Frontiers of Engineering Management

ISSN 2095-7513

ISSN 2096-0255(Online)

CN 10-1205/N

Postal Subscription Code 80-905

Front. Eng    2015, Vol. 2 Issue (3) : 266-276    https://doi.org/10.15302/J-FEM-2015048
Engineering Management Theories and Methodologies
Trapezoidal Intuitionistic Fuzzy Aggregation Operator Based on Choquet Integral and Its Application to Multi-Criteria Decision-Making Problems
Xi-hua Li(),Xiao-hong Chen
Business School of Central South University; Collaborative Innovation Center of Resource-conserving & Environment-friendly Society and Ecological Civilization, Changsha 410083, China
 Download: PDF(170 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

The Choquet integral can serve as a useful tool to aggregate interacting criteria in an uncertain environment. In this paper, a trapezoidal intuitionistic fuzzy aggregation operator based on the Choquet integral is proposed for multi-criteria decision-making problems. The decision information takes the form of trapezoidal intuitionistic fuzzy numbers and both the importance and the interaction information among decision-making criteria are considered. On the basis of the introduction of trapezoidal intuitionistic fuzzy numbers, its operational laws and expected value are defined. A trapezoidal intuitionistic fuzzy aggregation operator based on the Choquet integral is then defined and some of its properties are investigated. A new multi-criteria decision-making method based on a trapezoidal intuitionistic fuzzy Choquet integral operator is proposed. Finally, an illustrative example is used to show the feasibility and availability of the proposed method.

Keywords multi-criteria decision making      trapezoidal intuitionistic fuzzy numbers      Choquet integral      fuzzy measure      aggregation operator     
Corresponding Author(s): Xi-hua Li   
Online First Date: 16 March 2016    Issue Date: 21 March 2016
 Cite this article:   
Xi-hua Li,Xiao-hong Chen. Trapezoidal Intuitionistic Fuzzy Aggregation Operator Based on Choquet Integral and Its Application to Multi-Criteria Decision-Making Problems[J]. Front. Eng, 2015, 2(3): 266-276.
 URL:  
https://academic.hep.com.cn/fem/EN/10.15302/J-FEM-2015048
https://academic.hep.com.cn/fem/EN/Y2015/V2/I3/266
1 Abbasbandy, S., & Hajjari, T. (2009). A new approach for ranking of trapezoidal fuzzy number. Computers & Mathematics with Applications (Oxford, England), 57, 413–419
https://doi.org/10.1016/j.camwa.2008.10.090
2 Asady, B., & Zendehnam, A. (2007). Ranking fuzzy numbers by distance minimization. Applied Mathematical Modelling, 31, 2589–2598
https://doi.org/10.1016/j.apm.2006.10.018
3 Atanassov, K. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87–96
https://doi.org/10.1016/S0165-0114(86)80034-3
4 Chen, S., & Tan, J. (1994). Handling multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets and Systems, 67, 163–172
https://doi.org/10.1016/0165-0114(94)90084-1
5 Choquet, G. (1954). Theory of Capacities. Annales de l'Institut Fourier, 5, 131–295
https://doi.org/10.5802/aif.53
6 Dubois, D., & Prade, H. (1980). Fuzzy Sets and Systems: Theory and Application. New York: Academic Press
7 Grabisch, M. (1996a). The representation of importance and interaction of features by fuzzy measures. Pattern Recognition Letters, 17, 567–575
https://doi.org/10.1016/0167-8655(96)00020-7
8 Grabisch, M. (1996b). The application of fuzzy integrals in multicriteria decision making. European Journal of Operational Research, 89, 445–456
https://doi.org/10.1016/0377-2217(95)00176-X
9 Höhle, U. (1982). Integration with respect to fuzzy measures. In Anon. (Eds.), Proceedings of the IFAC Symposium on Theory and Application of Digital Control (pp. 35–37). New Delhi, India
10 Hong, D., & Choi, C. (2000). Multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets and Systems, 114, 103–113
https://doi.org/10.1016/S0165-0114(98)00271-1
11 Li, D. (2005). Multiattribute decision making models and methods using intuitionistic fuzzy sets. Journal of Computer and System Sciences, 70, 73–85
https://doi.org/10.1016/j.jcss.2004.06.002
12 Li, D., Wang, Y., Liu, S., & Shan, F. (2008). Fractional programming methodology for multi-attribute group decision making using IFS. Applied Soft Computing, 8, 219–225
13 Liu, H., & Wang, G. (2007). Multi-criteria decision-making methods based on intuitionistic fuzzy sets. European Journal of Operational Research, 179, 220–233
https://doi.org/10.1016/j.ejor.2006.04.009
14 Marichal, J., & Roubens, M. (1998). Dependence between criteria and multiple criteria decision aid. In 2nd International Workshop on Preferences and Decisions, Trento, Italy
15 Murofushi, T., & Sugeno, M. (1989). An interpretation of fuzzy measure and the Choquet integral as an integral with respect to a fuzzy measure. Fuzzy Sets and Systems, 29, 201–227
https://doi.org/10.1016/0165-0114(89)90194-2
16 Murofushi, T., & Sugeno, M. (1991). A theory of fuzzy measures–representations, the Choquet integral, and null sets. Journal of Mathematical Analysis and Applications, 159, 532–549
https://doi.org/10.1016/0022-247X(91)90213-J
17 Nehi, H., & Maleki, H. (2005). Intuitionistic fuzzy numbers and it’s applications in fuzzy optimization problem. In Proceedings of the 9th WSEAS International Conference on Systems, Athens, Greece, 1–5
18 Sugeno, M. (1974). Theory of fuzzy integral and its application (Doctorial dissertation). Tokyo: Tokyo Institute of Technology
19 Tan, C., & Chen, X. (2010). Intuitionistic fuzzy Choquet integral operator for multi-criteria decision making. Expert Systems with Applications, 37, 149–157
https://doi.org/10.1016/j.eswa.2009.05.005
20 Hadi-Vencheh, A., & Allame, M. (2010). On the relation between a fuzzy number and its centroid. Computers & Mathematics with Applications (Oxford, England), 59, 3578–3582
https://doi.org/10.1016/j.camwa.2010.03.051
21 Wang, J. (1995). Determining fuzzy measures by using statistics and neural networks, In Anon. (Eds.) Proc. of IFSA'95, Sao Paulo
22 Wang, J., & Zhang, Z. (2009). Aggregation operators on intuitionistic trapezoidal fuzzy number and its application to multicriteria decision making problems. Journal of Systems Engineering and Electronics, 20, 321–326
23 Wang, Z., Klir, G., & Wang, J. (1998). Neural networks used for determining belief measures and plausibility measures. Intelligent Automation and Soft Computing, 4, 313–324
https://doi.org/10.1080/10798587.1998.10750740
24 Wei, G. (2009). Some geometric aggregation functions and their application to dynamic multiple attribute decision making in the intuitionistic fuzzy setting. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems, 17, 179–196
https://doi.org/10.1142/S0218488509005802
25 Wu, J., & Zhang, Q. (2011). Multicriteria decision making method based on intuitionistic fuzzy weighted entropy. Expert Systems with Applications, 38, 916–922
https://doi.org/10.1016/j.eswa.2010.07.073
26 Xu, Z. (2007). Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making. Control and Decision, 22, 215–219 [in Chinese]
27 Xu, Z. (2010). Choquet integrals of weighted intuitionistic fuzzy information. Information Sciences, 180, 726–736
https://doi.org/10.1016/j.ins.2009.11.011
28 Xu, Z., & Yager, R. (2006). Some geometric aggregation operators based on intuitionistic fuzzy sets. International Journal of General Systems, 35, 417–433
https://doi.org/10.1080/03081070600574353
29 Xu, Z., & Yager, R. (2008). Dynamic intuitionistic fuzzy multi-attribute decision making. International Journal of Approximate Reasoning, 48, 246–262
https://doi.org/10.1016/j.ijar.2007.08.008
30 Yager, R.R. (1988). On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, 18, 183–190
https://doi.org/10.1109/21.87068
31 Ye, J. (2009). Multicriteria fuzzy decision-making method based on a novel accuracy function under interval-valued intuitionistic fuzzy environment. Expert Systems with Applications, 36, 6899–6902
https://doi.org/10.1016/j.eswa.2008.08.042
32 Ye, J. (2010). Fuzzy decision-making method based on the weighted correlation coefficient under intuitionistic fuzzy environment. European Journal of Operational Research, 205, 202–204
https://doi.org/10.1016/j.ejor.2010.01.019
33 Ye, J. (2011). Expected value method for intuitionistic trapezoidal fuzzy multicriteria decision-making problems. Expert Systems with Applications, 03, 059
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed