A novel method based on extended uncertain 2-tuple linguistic muirhead mean operators to MAGDM under uncertain 2-tuple linguistic environment

Yi Liu; Jun Liu; Ya Qin; Yang Xu

doi:10.2991/ijcis.d.190315.001

A novel method based on extended uncertain 2-tuple linguistic muirhead mean operators to MAGDM under uncertain 2-tuple linguistic environment

Yi Liu
, Jun Liu
, Ya Qin
, Yang Xu

Research output: Contribution to journal › Article › peer-review

14 Citations (Scopus)

77 Downloads (Pure)

Abstract

The present work is focused on multi-attribute group decision-making (MAGDM) problems with the uncertain 2-tuple linguistic information (ULI_2–tuple) based on new aggregation operators which can capture interrelationships of attributes by a parameter vector P. To begin with, we present some new uncertain 2-tuple linguistic MM aggregation (UL_2–tuple-MM) operators to handle MAGDM problems with ULI_2–tuple, including the uncertain 2-tuple linguistic Muirhead mean (UL_2–tuple-MM) operator, uncertain 2-tuple linguistic weighted Muirhead mean (UL_2–tuple-WMM) operator. In addition, we extend UL_2–tuple-WMM operator to a new aggregation operator named extended uncertain 2-tuple linguistic weighted Muirhead mean (EUL_2–tuple-WMM) operators in order to handle some decision-making problems with ULI_2–tuple whose attribute values are expressed in ULI_2–tuple and attribute weights are also 2-tuple linguistic information. Whilst, the some properties of these new aggregation operators are obtained and some special cases are discussed. Moreover, we propose a new method to solve the MAGDM problems with ULI_2–tuple. Finally, a numerical example is given to show the validity of the proposed method and the advantages of proposed method are also analysed.

Original language	English
Pages (from-to)	498-512
Number of pages	15
Journal	International Journal of Computational Intelligence Systems
Volume	12
Issue number	2
DOIs	https://doi.org/10.2991/ijcis.d.190315.001
Publication status	Published (in print/issue) - 29 Mar 2019

Bibliographical note

Funding Information:
This work is supported by National Natural Science Foundation of P.R.China (Grant no. 61673320, 61305074); Sichuan Province Youth Science and Technology Innovation Team (No. 2019JDTD0015); The Application Basic Research Plan Project of Sichuan Province (No.2017JY0199); The Scientific Research Project of Department of Education of Sichuan Province (18ZA0273, 15TD0027); Innovative Research Team of Neijiang Normal University (No. 18TD08).

Publisher Copyright:
© 2019 The Authors.

Funding

This work is supported by National Natural Science Foundation of P.R.China (Grant no. 61673320, 61305074); Sichuan Province Youth Science and Technology Innovation Team (No. 2019JDTD0015); The Application Basic Research Plan Project of Sichuan Province (No.2017JY0199); The Scientific Research Project of Department of Education of Sichuan Province (18ZA0273, 15TD0027); Innovative Research Team of Neijiang Normal University (No. 18TD08). Sichuan Province (No.2017JY0199); The Scientific Research Project of Department of Education of Sichuan Province (18ZA0273, 15TD0027); Innovative Research Team of Neijiang Normal University (No. 18TD08) This work is supported by National Natural Science Foundation of P.R.China (Grant no. 61673320, 61305074); Sichuan Province Youth Science and Technology Innovation Team (No. 2019JDTD0015); The Application Basic Research Plan Project of

Keywords

EUL-WMM operators
MAGDM
Modified uncertain 2-tuple linguistic representation model

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10.2991/ijcis.d.190315.001Licence: CC BY-NC

IJCIS_2019_AcceptedAuthor Accepted Manuscript, 180 KB

Cite this

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title = "A novel method based on extended uncertain 2-tuple linguistic muirhead mean operators to MAGDM under uncertain 2-tuple linguistic environment",

abstract = "The present work is focused on multi-attribute group decision-making (MAGDM) problems with the uncertain 2-tuple linguistic information (ULI2–tuple) based on new aggregation operators which can capture interrelationships of attributes by a parameter vector P. To begin with, we present some new uncertain 2-tuple linguistic MM aggregation (UL2–tuple-MM) operators to handle MAGDM problems with ULI2–tuple, including the uncertain 2-tuple linguistic Muirhead mean (UL2–tuple-MM) operator, uncertain 2-tuple linguistic weighted Muirhead mean (UL2–tuple-WMM) operator. In addition, we extend UL2–tuple-WMM operator to a new aggregation operator named extended uncertain 2-tuple linguistic weighted Muirhead mean (EUL2–tuple-WMM) operators in order to handle some decision-making problems with ULI2–tuple whose attribute values are expressed in ULI2–tuple and attribute weights are also 2-tuple linguistic information. Whilst, the some properties of these new aggregation operators are obtained and some special cases are discussed. Moreover, we propose a new method to solve the MAGDM problems with ULI2–tuple. Finally, a numerical example is given to show the validity of the proposed method and the advantages of proposed method are also analysed.",

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N1 - Funding Information: This work is supported by National Natural Science Foundation of P.R.China (Grant no. 61673320, 61305074); Sichuan Province Youth Science and Technology Innovation Team (No. 2019JDTD0015); The Application Basic Research Plan Project of Sichuan Province (No.2017JY0199); The Scientific Research Project of Department of Education of Sichuan Province (18ZA0273, 15TD0027); Innovative Research Team of Neijiang Normal University (No. 18TD08). Publisher Copyright: © 2019 The Authors.

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N2 - The present work is focused on multi-attribute group decision-making (MAGDM) problems with the uncertain 2-tuple linguistic information (ULI2–tuple) based on new aggregation operators which can capture interrelationships of attributes by a parameter vector P. To begin with, we present some new uncertain 2-tuple linguistic MM aggregation (UL2–tuple-MM) operators to handle MAGDM problems with ULI2–tuple, including the uncertain 2-tuple linguistic Muirhead mean (UL2–tuple-MM) operator, uncertain 2-tuple linguistic weighted Muirhead mean (UL2–tuple-WMM) operator. In addition, we extend UL2–tuple-WMM operator to a new aggregation operator named extended uncertain 2-tuple linguistic weighted Muirhead mean (EUL2–tuple-WMM) operators in order to handle some decision-making problems with ULI2–tuple whose attribute values are expressed in ULI2–tuple and attribute weights are also 2-tuple linguistic information. Whilst, the some properties of these new aggregation operators are obtained and some special cases are discussed. Moreover, we propose a new method to solve the MAGDM problems with ULI2–tuple. Finally, a numerical example is given to show the validity of the proposed method and the advantages of proposed method are also analysed.

AB - The present work is focused on multi-attribute group decision-making (MAGDM) problems with the uncertain 2-tuple linguistic information (ULI2–tuple) based on new aggregation operators which can capture interrelationships of attributes by a parameter vector P. To begin with, we present some new uncertain 2-tuple linguistic MM aggregation (UL2–tuple-MM) operators to handle MAGDM problems with ULI2–tuple, including the uncertain 2-tuple linguistic Muirhead mean (UL2–tuple-MM) operator, uncertain 2-tuple linguistic weighted Muirhead mean (UL2–tuple-WMM) operator. In addition, we extend UL2–tuple-WMM operator to a new aggregation operator named extended uncertain 2-tuple linguistic weighted Muirhead mean (EUL2–tuple-WMM) operators in order to handle some decision-making problems with ULI2–tuple whose attribute values are expressed in ULI2–tuple and attribute weights are also 2-tuple linguistic information. Whilst, the some properties of these new aggregation operators are obtained and some special cases are discussed. Moreover, we propose a new method to solve the MAGDM problems with ULI2–tuple. Finally, a numerical example is given to show the validity of the proposed method and the advantages of proposed method are also analysed.

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A novel method based on extended uncertain 2-tuple linguistic muirhead mean operators to MAGDM under uncertain 2-tuple linguistic environment

Abstract

Bibliographical note

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Keywords

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