科研之友
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摘要
Hesitant fuzzy linguistic preference relation (HFLPR) is a new preference structure that the decision makers (DMs) are hesitant about several possible linguistic terms of preference information for pairwise comparison between alternatives. This paper examines the additive consistency of HFLPR with a new expansion principle for hesitant fuzzy linguistic term sets (HFLTSs). In order to normalize HFLTSs with different numbers of linguistic terms, a least common multiple expansion (LCME) principle is proposed. According to the LCME principle, the additive consistent index of an HFLPR is defined to measure the consistency level of the HFLPR. For improving the unacceptable additive consistency of an HFLPR, a pure integer programming model is constructed to derive an acceptable additive consistent HFLPR. In group decision making (GDM) with HFLPRs, the similarities between DMs are calculated based on their individual HFLPR with acceptable additive consistency. Subsequently, the confidence degrees of DMs are defined to derive DMs' weights, and some examples including an investment project management problem are analyzed to verify the effectiveness of the proposed method.
