Abstract
In order to solve multiple-attribute group decision-making (MAGDM) problems under a trapezoid intuitionistic fuzzy linguistic (TIFL) environment and the relationships between multiple input parameters needed, in this paper, we extend the Maclaurin symmetric mean (MSM) operators to TIFL numbers (TIFLNs). Some new aggregation operators are proposed, including the trapezoid intuitionistic fuzzy linguistic Maclaurin symmetric mean (TIFLMSM) operator, trapezoid intuitionistic fuzzy linguistic generalized Maclaurin symmetric mean (TIFLGMSM) operator, trapezoid intuitionistic fuzzy linguistic weighted Maclaurin symmetric mean (TIFLWMSM) operator and trapezoid intuitionistic fuzzy linguistic weighted generalized Maclaurin symmetric mean (TIFLWGMSM) operator. Next, based on the TIFLWMSM and TIFLWGMSM operators, two methods are presented to deal with MAGDM problems. Finally, there is a numerical example to verify the effectiveness and feasibility of the proposed approaches.
Highlights
As an important branch of modern decision science, the multiple-attribute group decision-making (MAGDM) problems have widely existed in various areas, such as economics, management, military, society and so on
Xu [6] defined uncertain linguistic variables (LVs) (ULVs) based on LVs and proposed two uncertain linguistic aggregation operators to deal with MAGDM problems under the uncertain linguistic environment
We firstly compare the two methods presented in this paper with other methods, which include Chu et al.’s [20] proposed trapezoid intuitionistic fuzzy linguistic weighted Bonferroni mean (TIFLWBM) and TIFLWGBM operators and the ITrFLWA and ITrFLOWA operators developed by Ju et al [15]
Summary
As an important branch of modern decision science, the MAGDM problems have widely existed in various areas, such as economics, management, military, society and so on. Xu [6] defined uncertain LVs (ULVs) based on LVs and proposed two uncertain linguistic aggregation operators to deal with MAGDM problems under the uncertain linguistic environment. In the real decision-making process, DMs have difficultly expressing their ideas clearly by utilizing LVs or IFSs. Wang and Li [11] further extended LVs and IFSs to the intuitionistic fuzzy linguistic set (ILS). In order to avoid the above defect, Maclaurin [19] firstly presented the MSM operator, which has the characteristic of considering the correlations among multiple input parameters. Qin and Liu [26] extended the MSM operator to the intuitionistic fuzzy environment and applied it to deal with intuitionistic fuzzy MAGDM problems. Based on the intuitionistic fuzzy set and LTS, IFLS was proposed by Wang and Li [9], as shown below. Based on TIFLNs and MSM operators, we developed the TILFMSM operator, TIFLGMSM operator, TIFLWMSM operator and TIFLWGMSM operator
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