Abstract
Flexible linguistic expression (FLE) is a complex linguistic representation that almost generalizes all distributed representations, posing the following challenges for the personalized individual semantics (PIS) issues in group decision-making (GDM) with FLEs. (1) The available measurement methods for FLEs are limited and suffer from some unreasonable or poorly discriminated deficiencies. (2) The existing research on FLEs has failed to fully utilize decision information incorporating subjective preferences and objective information, and the format of FLEs may be altered when optimizing PISs. To address these challenges, this paper focuses on the GDM problems under subjective preferences and objective information, both of which are characterized by FLEs, and introduces a novel FLE-based GDM method with PIS. Firstly, a new similarity measure for FLEs is proposed, considering both external and internal characteristics, namely semantics, elements, and symbolic proportions of linguistic term subsets. Secondly, by utilizing the similarity between the decision-maker's preference matrix and decision matrix, as well as the consistency of the preference matrix, a PIS optimization model is constructed to determine the personalized semantics of individual decision-makers. Subsequently, an optimization model is constructed, focused on maximizing the consensus level to determine the differentiated weights of decision-makers. Furthermore, individual evaluation information is aggregated into group evaluation information, a personalized semantic model is constructed to determine the personalized semantics of the group, and the selection process for alternatives is implemented. Finally, the effectiveness and advantages of our method are illustrated through its application in airline service quality assessment and by comparing it with alternative approaches.
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