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The dynamic multiple attribute decision making problems with linguistic information are investigated. A new aggregation operator called dynamic linguistic weighted averaging (DLWA) operator is presented. Based on the DLWA and LWAA operators, we develop a procedure to solve the we develop an approach to the dynamic linguistic multiple attribute decision making (DL-MADM) problems where all decision...
Aggregation operators for linguistic variables usually assume a uniform and symmetrical distribution of the linguistic terms that define the variable. A well-known aggregation operator is the Linguistic Ordered Weighted Average (LOWA), which has been extensively applied. However, there are some problems where an unbalanced set of linguistic terms is more appropriate to describe the objects. In this...
With respect to multiple attribute decision making problems with linguistic information, a decision analysis is proposed. A new aggregation operator is proposed: the 2-tuple linguistic weighted harmonic averaging (T-WHA) operator and properties of the operators are analyzed. Then, a method based on the T-WHA operator for multiple attribute decision making is presented. In this approach, alternative...
In this paper, an approach based on multi-granularity linguistic assessment information is used to select IT project. Firstly, the expert linguistic assessment information is represented in the form of 2-tuple. Secondly, the basic linguistic term set is chosen from multi-granularity linguistic term sets. Then, based on the 2-tuple order weighted averaging (TOWA) and other aggregation operator, the...
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