A Novel Method Based on Extended Uncertain 2-tuple Linguistic Muirhead Mean Operators to MAGDM under Uncertain 2-Tuple Linguistic Environment

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-tupleWMM) 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. (c) 2019 The Authors. Published by Atlantis Press SARL.