Group Generalized Interval-valued Intuitionistic Fuzzy Soft Sets and Their Applications in\\ Decision Making

Document Type : Research Paper

Authors

1 Key Laboratory of Ultrafast Photoelectric Diagnostics Technology, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an, China and University of Chinese Academy of Sciences, Beijing, China.

2 Key Laboratory of Ultrafast Photoelectric Diagnostics Technology, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an, China

Abstract

Interval-valued intuitionistic fuzzy sets (IVIFSs) are widely used to handle uncertainty and imprecision in decision making. However, in more complicated environment, it is difficult to express the uncertain information by an IVIFS with considering the decision-making preference. Hence, this paper proposes a group generalized interval-valued intuitionistic fuzzy soft set (G-GIVIFSS) which contains the basic description by interval-valued intuitionistic fuzzy soft set (IVIFSS) on the alternatives and a group of experts' evaluation of it. It contributes the following threefold: 1) A generalized interval-valued intuitionistic fuzzy soft set (GIVIFSS) is proposed by introducing an interval-valued intuitionistic fuzzy parameter, which reflects a new and senior expert's opinion on the basic description. The operations, properties and aggregation operators of GIVIFSS are discussed. 2) Based on GIVIFSS, a G-GIVIFSS is then proposed to reduce the impact of decision-making preference by introducing more parameters by a group of experts. Its important operations, properties and the weighted averaging operator are also defined. 3) A multi-attribute group decision making model based on G-GIVIFSS weighted averaging operator is built to solve the group decision making problems in the more universal IVIF environment, and two practical examples are taken to validate the efficiency and effectiveness of the proposed model.

Keywords


[1] M. Agarwal, K. Biswas and M. Hanmandlu, Generalized intuitionistic fuzzy soft sets with
applications in decision-making, Applied Soft Computing, 13(8) (2013), 3552{3566.
[2] M. Ali, F. Feng, X. Liu, W. Min and M. Shabir, On some new operations in soft set theory,
Computers & Mathematics with Applications, 57(9) (2009), 1547{1553.
[3] M. Ali and M. Shabir, Logic connective for soft sets and fuzzy soft sets, IEEE Trancsactions
on Fuzzy Systems, 22(6) (2014), 1431{1442.
[4] K. Atanassov, Intuitionistic fuzzy sets, Intuitionistic Fuzzy Sets, 20(1) (1986), 87{96.
[5] K. Atanassov and G. Gargov, Interval-valued intuitionistic fuzzy sets, Fuzzy Sets Systems,
31(3) (1989), 343{349.
[6] L. Chen and C. Tu, Dominance-Based Ranking Functions for Interval-Valued Intuitionistic
Fuzzy Sets, IEEE Trancsactions on Cybernetics, 44(8) (2014), 1269{1282.
[7] S. Das and S. Kar, Group decision making in medical system: an intuitionistic fuzzy soft set
approach, Applied Soft Computing, 24 (2014), 196{211.
[8] B. Dinda and T. Bera and T. Samanta, Generalised intuitionistic fuzzy soft sets and its
application in decision making, arXiv preprint arXiv:1010.2468, 2010.
[9] S. Ebrahimnejad and H. Hashemi and S. Mousavi and B. Vahdani, A new interval-valued
intuitionistic fuzzy model to group decision making for the selection of outsourcing providers,
Economic Computation and Economic Cybernetics Studies and Research, 49(2) (2015), 269{
290.
[10] F. Feng and C. Li and B. Davvaz and M. Ali, Soft sets combined with fuzzy sets and rough
sets: a tentative approach, Soft Computing, 14(9) (2010), 899{911.
[11] H. Hashemi, J. Bazargan, S. Mousavi and B. Vahdani, An extended compromise ratio model
with an application to reservoir
ood control operation under an interval-valued intuitionistic
fuzzy environment, Applied Mathematical Modelling, 38(14) (2014), 3495{3511.
[12] Y. Jiang, Y. Tang,Q. Chen, H. Liu and J. Tang, Interval-valued intuitionistic fuzzy soft sets
and their properties, Computers & Mathematics with Applications, 60(3) (2010), 906{918.
[13] F. Jin, L. Pei, H. Chen and L. Zhou, Interval-valued intuitionistic fuzzy continuous weighted
entropy and its application to multi-criteria fuzzy group decision making, Knowledge-Based
Systems, 59 (2014), 132{141.
[14] P. Liu, Some hamacher aggregation operators based on the interval-valued intuitionistic fuzzy
numbers and their application to group decision making, IEEE Transaction on Fuzzy Systems,
22(1) (2014), 83{97.
[15] X. Ma, H. Qin, N. Sulaiman, T. Herawan and J. Abawajy, The parameter reduction of
the interval-valued fuzzy soft sets and its related algorithms, IEEE trancsactions on Fuzzy
Systems, 22(1) (2014), 57{71.
[16] P. Maji, R. Biswas and A. Roy, Fuzzy soft sets, Journal of Fuzzy Mathematics, 9(3) (2001),
589{602.
[17] P. Maji, R. Biswas and A. Roy, Intuitionistic fuzzy soft sets, Journal of Fuzzy Mathematics,
9(3) (2001), 677{692.
[18] P. Maji and R. Biswas and A. Roy, Soft set theory, Computers & Mathematics with Appli-
cations, 45(4) (2003), 555{562.
[19] P. Majumdar and S. Samanta, Similarity measure of soft sets, New Mathematics and Natural
Computation, 4(1) (2008), 1{12.
[20] P. Majumdar and S. Samanta, Generalised fuzzy soft sets, Computers & Mathematics with
Applications, 59(4) (2010), 1425{1432.
[21] F. Meng, X. Chen and Q. Zhang, Some interval-valued intuitionistic uncertain linguistic
Choquet operators and their application to multi-attribute group decision making, Applied
Mathematical Modelling, 38(9) (2014), 2543{2557.
[22] D. Molodtsov, Soft set theory- rst results, Computers & and Mathematics with Applications,
37(4) (1999), 19{31.
[23] S. Mousavi, B. Vahdani and S. Behzadi, Designing a model of intuitionistic fuzzy VIKOR
in multi-attribute group decision-making problems, Iranian Journal of Fuzzy Systems, 13(1)
(2016), 45{65.
[24] S. Mousavi and B. Vahdani, Cross-docking location selection in distribution systems: a new
intuitionistic fuzzy hierarchical decision model, International Journal of Computational In-
telligence Systems, 9(1) (2016), 91{109.
[25] S. Mousavi and H. Gitinavard and B. Vahdani, Evaluating construction projects by a new
group decision-making model based on intuitionistic fuzzy logic concepts, International Jour-
nal of Engineering-Transactions C: Aspects, 28(9) (2015), 1312{1319.
[26] A. Roy and P. Maji, A fuzzy soft set theoretic approach to decision making problems, Journal
of Computational and Applied Mathematics, 203(2) (2007), 412{418.
[27] B. Vahdani, S. Mousavi, R. Tavakkoli-Moghaddam and H. Hashemi, A new design of the
elimination and choice translating reality method for multi-criteria group decision-making in
an intuitionistic fuzzy environment, Applied Mathematical Modelling, 37(4) (2013), 1781{
1799.
[28] W. Wang and X. Liu, The multi-attribute decision making method based on interval-valued
intuitionistic fuzzy Einstein hybrid weighted geometric operator, Computers & Mathematics
with Applications, 66(10) (2013), 1845{1856.
[29] H.Wu and X. Su, Threat assessment of aerial targets based on group generalized intuitionistic
fuzzy soft sets, Control and Decision, 30(8) (2015), 1462{1468.
[30] J. Wu and F. Chiclana, A risk attitudinal ranking method for interval-valued intuitionistic
fuzzy numbers based on novel attitudinal expected score and accuracy functions, Applied Soft
Computing, 22 (2014), 272{286.
[31] Z. Xu, Method for aggregating interval-valued intuitionistic fuzzy information and their ap-
plication to decision making, Control and Decision, 22(2) (2007), 215{219.
[32] Z. Xu, A method based on distance measure for interval-valued intuitionistic fuzzy group
decision making, Information Sciences, 180(1) (2010), 181{190.
[33] Z. Xu and J. Chen, An approach to group decision making based on intervalvalued intuition-
istic judgment matrices, Systems Engineering-Theory & Practice, 27(4) (2007), 126{133.
[34] Z. Yue, A group decision making approach based on aggregating interval data into interval-
valued intuitionistic fuzzy information, Applied Mathematical Modelling, 38(2) (2014), 683{
698.
[35] Z. Yue and Y. Jia, A group decision making model with hybrid intuitionistic fuzzy informa-
tion, Computers & Industrial Engineering, 87 (2015), 202{212.
[36] L. Zadeh, Fuzzy sets, Information and Control, 8(3) (1965), 338{353.
[37] X. Zhang and Z. Xu, Soft computing based on maximizing consensus and fuzzy TOPSIS ap-
proach to interval-valued intuitionistic fuzzy group decision making, Applied Soft Computing,
26 (2015), 42{56.