Multiple attribute decision making with triangular intuitionistic fuzzy numbers based on zero-sum game approach

Document Type : Research Paper

Authors

1 College of Modern Economics & Management, Jiangxi University of Finance and Economics, Nanchang 330013, China

2 School of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, China

3 College of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, China

Abstract

For many decision problems with uncertainty, triangular intuitionistic fuzzy number is a useful tool in expressing ill-known quantities. This paper develops a novel decision method based on zero-sum game for multiple attribute decision making problems where the attribute values take the form of triangular intuitionistic fuzzy numbers and the attribute weights are unknown. First, a new value index is defined for triangular intuitionistic fuzzy numbers on the basis of the centroid. Thereby, a new ranking approach is presented for comparing triangular intuitionistic fuzzy numbers. We formulate a multiple attribute decision making problem as a two-person zero-sum game with payoffs of triangular intuitionistic fuzzy numbers. Then, following the new ranking approach, the fuzzy matrix game is converted as a pair of crisp linear programming models, and the optimal strategies are objectively derived by solving such models. Therefore, the ranking order of alternatives is determined by the expected scores of alternatives. An example of video monitoring system selection is demonstrated to illustrate the effectiveness of the proposed methodology.

Keywords


[1] T. Allahviranloo, R. Saneifard, Defuzzi fication method for ranking fuzzy numbers based on center of gravity, Iranian
Journal of Fuzzy Systems, 9(6) (2012), 57–67.
[2] K. Atanassov, G. Gargov, Interval valued intuitionistic fuzzy sets, Fuzzy sets and systems, 31(3) (1989), 343–349.
[3] K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets Systems, 20(1) (1996), 87–96.
[4] A. Baykasoglu, Ilker Golcuk, Fuzzy sets, Information and control, 8(3) (1965), 338–353.
[5] Y. W. Chen, M. Larbani, Two-person zero-sum game approach for fuzzy multiple attribute decision making problems,
Fuzzy Sets Systems, 157(1) (2006), 34–51.
[6] R. Csutora, J. J. Buckley, Fuzzy hierarchical analysis: the Lambda-Max method, Fuzzy sets Systems, 120(2) (2001),
181–195.
[7] M. Erdogan, I. Kaya, An integrated multi-criteria decision-making methodology based on type-2 fuzzy sets for selec-
tion among energy alternatives in turkey, Iranian Journal of Fuzzy Systems, 12(1) (2015), 1–25.
[8] O. Jadidi, S. Zolfaghari, S. Cavalieri, A new normalized goal programming model for multi-objective problems: a case
of supplier selection and order allocation, International Journal of Production Economics, 148(1) (1965), 158–165.
[9] J. Jiang, X. Li, Y. W. Chen, D. W. Tang, A goal programming approach to group decision making with incom-
plete fuzzy and interval preference relations, International Journal of Uncertainty, Fuzziness and Knowledge-Based
Systems, 20(3) (2012), 355–367.
[10] M. Larbani, Solving bimatrix games with fuzzy payoffs by introducing Nature as a third player, Fuzzy Sets Systems,
160(5) (2009), 657–666.
[11] D. F. Li, J. X. Nan, M. J. Zhang, A ranking method of triangular intuitionistic fuzzy numbers and application to
decision making, International Journal of Computational Intelligence Systems, 3(5) (2010), 522–530.
[12] D. F. Li, A ratio ranking method of triangular intuitionistic fuzzy numbers and its application to MADM problems,
Computers & Mathematics with Applications, 60(6) (2010), 522–530.
[13] R. Lin, X. F. Zhao, G. W. Wei, Fuzzy number intuitionistic fuzzy prioritized operators and their application to
multiple attribute decision making, Journal of Intelligent and Fuzzy Systems, 24(4) (2013), 879–888.
[14] H. W. Liu, G. J. Wang, Multi-criteria decision-making methods based on intuitionistic fuzzy sets, European Journal
of Operational Research, 179(1) (2007), 220–233.
[15] P. D. Liu, F. Jin, The trapezoid fuzzy linguistic bonferroni mean operators and their application to multiple attribute
decision making, Scientia Iranica, 19(6) (2015), 1947–1959.
[16] Y. X. Ma, J. Wang, J. Q. Wang, X. H. Chen, Y. X. Ma, J. Wang, et al, Two-tuple linguistic aggregation opera-
tors based on subjective sensation and objective numerical scales for multi-criteria group decision-making problem,
Scientia Iranica, 23(3) (2016), 1399–1417.
[17] A. R. Mishra, P. Rani, D. Jain, Information measure based TOPSIS for multicriteria decision making problem in
intuitionistic fuzzy environment, Iranian Journal of Fuzzy Systems, 14(6) (2017), 41–63.
[18] J. X. Nan, D. F. Li, M. J. Zhang, A lexicographic method for matrix games with payoffs of triangular intuitionistic
fuzzy numbers, International Journal of Computational Intelligence Systems, 3(3) (2010), 280–289.
[19] Z. Pei, L. Zheng, A novel approach to multi-attribute decision making based on intuitionistic fuzzy sets, Expert
Systems with Applications, 39(3) (2012), 2560–2566.
[20] Z. Pei, A note on the TOPSIS method in MADM problems with linguistic evaluations, Applied Soft Computing,
36(C) (2015), 24–35.
[21] P. Rao, N. R. Shankar, Ranking fuzzy numbers with a distance method using circumcenter of centroids and an
index of modality, Advances in Fuzzy Systems, 3 (2011), 1–7.
[22] J. Robinson, Multiple attribute group decision analysis for intuitionistic triangular and trapezoidal fuzzy numbers,
International Journal of Fuzzy System Applications, 5(3) (2016), 42–76.
[23] A. Schrijver, Theory of linear and integer programming, John Wiley & Sons, England, 1998.
[24] G. B. Thomas, R. L. Finney, M. D. Weir, Calculus and analytic geometry, Reading Addison-Wesley, Massachusetts,
1984.
[25] S. P. Wan, Interval Multi-attribute Decision-making Method Based on Game Theory, Systems Engineering, 28(1)
(2010), 17–20.
[26] S. P. Wan, Multi-attribute decision making method based on possibility variance coefficient of triangular intuition-
istic fuzzy numbers, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 21(2) (2013),
223–243.
[27] S. P. Wan, Q. Y. Wang, J. Y. Dong, The extended VIKOR method for multi-attribute group decision making with
triangular intuitionistic fuzzy numbers, Knowledge-Based Systems, 52(6) (2013), 65–77.
[28] S. P. Wan, D. F. Li, Possibility mean and variance based method for multi-attribute decision making with triangular
intuitionistic fuzzy numbers, J. Intelligent and Fuzzy Systems, 24(4) (2013), 743–754.
[29] S. P. Wan, D. F. Li, Fuzzy mathematical programming approach to heterogeneous multiattribute decision-making
with interval-valued intuitionistic fuzzy truth degrees, Information Sciences, 325 (2015), 484–503.
[30] S. P. Wan, J. Xu, J. Y. Dong, Aggregating decision information into interval-valued intuitionistic fuzzy numbers
for heterogeneous multi-attribute group decision making, Knowledge-Based Systems, 113(C) (2016), 155–170.
[31] S. P. Wan, Z. H. Yi, Power average of trapezoidal intuitionistic fuzzy numbers using strict t-norms and t-conorms,
IEEE Transactions on Fuzzy Systems, 24(5) (2016), 1035–1047.
[32] S. P. Wan, Y. J. Zhu, Triangular Intuitionistic Fuzzy Triple Bonferroni Harmonic Mean Operators and Application
to Multi-attribute Group Decision Making, Iranian Journal of Fuzzy Systems, 13(5)(2016), 117–145.
[33] S. P. Wan, G. L. Xu, F. Wang, J. Y. Dong, A new method for Atanassovs interval-valued intuitionistic fuzzy
MAGDM with incomplete attribute weight information, Information Sciences, 316(C) (2016), 329–347.
[34] S. P. Wan, J. Xu, A method for multi-attribute group decision making with triangular intuitionistic fuzzy numbers
and application to trustworthy service selection, Scientia Iranica, 24(2) (2017), 794–807.
[35] J. J. Wang, Y. Y. Jing, C. F. Zhang, J. H. Zhao, Review on multi-criteria decision analysis aid in sustainable
energy decision-making, 13(9) (2009), 2263–2278
[36] L. E. Wang, H. C. Liu, M. Y. Quan, Evaluating the risk of failure modes with a hybrid MCDM model under
interval-valued intuitionistic fuzzy environments, Computer Industrial Engineering, 102 (2016), 175–185.
[37] X. Wang, J. Wang, X. Chen, Fuzzy multi-criteria decision making method based on fuzzy structured element with
incomplete weight information, Iranian Journal of Fuzzy Systems, 13(2) (2016), 1–17.
[38] G. Wei, X. Zhao, R. Lin, H. Wang, Generalized triangular fuzzy correlated averaging operator and their application
to multiple attribute decision making, Applied Mathematical Modelling, 36(7) (2012), 2975–2982.
[39] D. J. White, Fuzzy multiple criteria decision making: Recent developments, 78(2)(1996), 139–153.
[40] Y. X. Xue, J. X. You, X. D. Lai, H. C. Liu, An interval-valued intuitionistic fuzzy MABAC approach for material
selection with incomplete weight information, Applied Soft Computing, 38 (2016), 703–713.
[41] Z. H. Xu, R. R. Yager, Dynamic intuitionistic fuzzy multi-attribute decision making, Springer Berlin Heidelberg,
48(1) (2012), 246–262.
[42] J. Xu, S. P. Wan, J. Y. Dong, Aggregating decision information into Atanassov's intuitionistic fuzzy numbers for
heterogeneous multi-attribute group decision making, Applied Soft Computing, 41 (2016), 331–351.
[43] W. E. Yang, J. Q. Wang, Vague linguistic matrix game approach for multi-criteria decision making with uncertain
weights, Journal of Intelligent & Fuzzy Systems, 25(2) (2013), 315–324.
[44] L. A. Zadeh, Fuzzy sets, Information and control, 8(3) (1965), 338–353.
[45] M. J. Zhang, J. X. Nan, D. F. Li, Y. X. Li, TOPSIS for MADM with triangular intuitionistic fuzzy numbers,
Operations Research and Management Science, 21 (2012), 96–101.
[46] H. Zhao, J. X. You, H. C. Liu, Failure mode and effect analysis using MULTIMOORA method with continuous
weighted entropy under interval-valued intuitionistic fuzzy environment, Soft Computing, 21(18) (2017), 5355–5367.
[47] J. Zhao, X. Y. You, H. C. Liu, S. M.Wu, An extended VIKOR method using intuitionistic fuzzy sets and combination
weights for supplier selection, Symmetry, 9(9) (2017), 169.