2-Tuple Linguistic Induced Generalized Weighted Distance Operators and Their Application to Decision Making

In this paper, based on the induced ordered weighted distance(IOWD) measure, we present a wide range of 2-tuple linguistic induced generalized weighted distance operators. Firstly, we introduce the 2-tuple linguistic induced generalized ordered weighted distance(2TLIGOWD) operator, which is a generalization of the classical induced ordered weighted averaging(IOWA) operator that uses 2-tuple linguistic information, distance measures, and the generalized mean in order to provide some more general formulations. The main advantage of the operator is that it is able to deal with uncertain environment where the information is very imprecise and can be assessed with 2-tuple linguistic information. We study some desirable properties of the proposed aggregation operator and investigate its special cases. Furthermore, we generalize the 2TLIGOWD operator using the Choquet integral, and get the 2TLIGCOWD operator. The prominent characteristic of the operator is that it cannot only consider the importance of the elements or their ordered positions, but also can reflect the correlation among the elements. In addition, we further generalize the 2TLIGOWD operator and 2TLIGCOWD operator by using the hybrid averaging and the quasi-arithmetic mean getting more general aggregation operators. Finally, we present an application of the 2TLIGCOWD operator in a decision making concerning the selection of strategies with 2tuple linguistic information. 1This work is supported by the foundation of National Natural Science Foundation of China (No. 11601475, 11671228), the foundation of First Class Discipline of Zhejiang-A(Zhejiang University of Finance and EconomicsStatistics), the foundation of National Natural Science Foundation of Shandong Province (No. ZR2016AI05) and Scientific Research Project of Shandong Universities (No. J15LI11). The second author Min Sun is the corresponding author of this work. *AMO-Advanced Modeling and optimization. ISSN: 1841-4311