The multiple attribute group decision making (MAGDM) problem, in which both the attribute weights and the expert weights are correlated and the attribute values take the form of interval grey linguistic (IGL) variables, is investigated in this paper. First, based on the relative concepts of IGL variables and the operation rules between IGL variables, two new aggregation operators are developed, which are the interval grey linguistic correlated ordered geometric (IGLCOG) operator and the induced interval grey linguistic correlated ordered geometric (I-IGLCOG) operator. Then, some desirable properties of the I-IGLCOG operator are studied, such as commutativity, idempotency, monotonicity and boundedness. Next, the IGLCOG and I-IGLCOG operator-based approaches are developed to solve the abovementioned MAGDM problem. Finally, an illustrative examples are given to verify the developed approach and demonstrate its practicality and effectiveness.
LiuP. and LiuY., An approach to multiple attribute group decision making based on intuitionistic trapezoidal fuzzy power generalized aggregation operator, International Journal of Computational Intelligence Systems7 (2014), 291–304.
2.
MousaviS.M., JolaiF. and Tavakkoli-MoghaddamR., A fuzzy stochastic multi-attribute group decision-making approach for selection problems, Group Decision and Negotiation22 (2013), 207–233.
3.
SuZ., XiaG., ChenM. and WangL., Induced generalized intuitionistic fuzzy OWA operator for multi-attribute group decision making, Expert Systems with Applications39 (2012), 1902–1910.
4.
WanS.P. and DongJ.Y., Interval-valued intuitionistic fuzzy mathematical programming method for hybrid multi-criteria group decision making with interval-valued intuitionistic fuzzy truth degrees, Information Fusion26 (2015), 49–65.
5.
WeiG.W., Grey relational analysis method for 2-tuple linguistic multiple attribute group decision making with incomplete weight information, Expert Systems with Applications38 (2011), 4824–4828.
6.
WeiG.W. and ZhaoX., Some induced correlated aggregating operators with intuitionistic fuzzy information and their application to multiple attribute group decision making, Expert Systems with Applications39 (2012), 2026–2034.
7.
WuJ., CaoQ. and ZhangJ., Some properties of the induced continuous ordered weighted geometric operators in group decision making, Computers & Industrial Engineering59 (2010), 100–106.
8.
XuZ.S., A note on linguistic hybrid arithmetic averaging operator in multiple attribute group decision making with linguistic information, Group Decision and Negotiation15 (2006), 593–604.
9.
ZhangG., DongY. and XuY., Linear optimization modeling of consistency issues in group decision making based on fuzzy preference relations, Expert Systems with Applications39 (2012), 2415–2420.
10.
ZhangZ., Hesitant fuzzy power aggregation operators and their application to multiple attribute group decision making, Information Sciences234 (2013), 150–181.
11.
ZadehL.A., Fuzzy sets, Information and Control8 (1965), 338–353.
12.
DengJ.L., Control problems of grey systems, Systems & Control Letters1 (1982), 288–294.
13.
MerigóJ.M., CasanovasM. and MartínezL., Linguistic aggregation operators for linguistic decision making based on the Dempster-Shafer theory of evidence, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems18(3) (2010), 287–304.
14.
MerigóJ.M. and Gil-LafuenteA.M., Induced 2-tuple linguistic generalized aggregation operators and their application in decision-making, Information Sciences236 (2013), 1–16.
15.
XuY.J., ShiP., MerigóJ.M. and WangH.M., Some proportional 2-tuple geometric aggregation operators for linguistic decision making, Journal of Intelligent & Fuzzy Systems25(3) (2013), 833–843.
16.
LiuP. and JinF., The multi-attribute group decision making method based on the interval grey linguistic variables, African Journal of Business Management4 (2010), 3708–3715.
17.
LiuP.D. and ZhangX., The multi-attribute group decision making method based on the interval grey linguistic variables weighted geometric aggregation operator, Control and Decision26 (2011), 743–747.
18.
XuZ.S., Choquet integrals of weighted intuitionistic fuzzy information, Information Sciences180 (2010), 726–736.
19.
TanC. and ChenX., Induced choquet ordered averaging operator and its application to group decision making, International Journal of Intelligent Systems25 (2010), 59–82.
20.
YagerR.R., Induced aggregation operators, Fuzzy Sets And Systems137 (2003), 59–69.
21.
YagerR.R., OWA aggregation over a continuous interval argument with applications to decision making, IEEE Transactions On Systems Man And Cybernetics Part B-Cybernetics34 (2004), 1952–1963.
22.
WangZ. and KlirG., Fuzzy measure theory, Plenum Publishing Corporation, 1992.
23.
XuZ.S. and DaQ.L., An overview of operators for aggregating information, International Journal of Intelligent Systems18 (2003), 953–969.
