A Novel Method Based on Extended Uncertain 2-tuple Linguistic Muirhead Mean Operators to MAGDM under Uncertain 2-Tuple Linguistic Environment
- 10.2991/ijcis.d.190315.001How to use a DOI?
- Modified uncertain 2-tuple linguistic representation model; EUL2–tuple-WMM operators; MAGDM
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.
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Yi Liu AU - Jun Liu AU - Ya Qin AU - Yang Xu PY - 2019 DA - 2019/03/29 TI - A Novel Method Based on Extended Uncertain 2-tuple Linguistic Muirhead Mean Operators to MAGDM under Uncertain 2-Tuple Linguistic Environment JO - International Journal of Computational Intelligence Systems SP - 498 EP - 512 VL - 12 IS - 2 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.190315.001 DO - 10.2991/ijcis.d.190315.001 ID - Liu2019 ER -