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    考虑关联性与优先关系的区间犹豫模糊图决策

    Interval-Valued Hesitant Fuzzy Graphs Decision Making with Correlations and Prioritization Relationships

    • 摘要: 区间犹豫模糊集是区间数和犹豫模糊集的推广,通常用以描述不确定信息具备的不完备性与犹豫性.近年来,区间犹豫模糊多属性决策问题受到了学者们的广泛关注.针对属性间同时具有关联性与优先关系的区间犹豫模糊多属性决策问题,利用模糊图可通过顶点间的边表示属性间关联性的优势,研究基于区间犹豫模糊图的多属性决策方法.首先从定义、运算规则及映射关系的角度建立区间犹豫模糊图的相关概念.在此基础上,提出考虑关联性与优先关系的区间犹豫模糊图多属性决策方法.最后用实例及对比性分析阐述所提多属性决策方法的可行性与有效性.结果表明:相较于经典区间犹豫模糊多属性决策方法,所提方法能够合理求解属性间同时具有关联性与优先关系的区间犹豫模糊多属性决策问题.

       

      Abstract: Interval-valued hesitant fuzzy sets are generalizations of interval numbers and hesitant fuzzy sets, which are usually used to depict the incompleteness and hesitancy in uncertain information. In recent years, interval-valued hesitant fuzzy multi-attribute decision making problems have received extensive attentions of scholars. In allusion to interval-valued hesitant fuzzy multi-attribute decision making problems that are possessed with correlations and prioritization relationships between attributes at the same time, by taking advantages of fuzzy graphs could represent the correlations between attributes through edges between vertices, this paper studies multi-attribute decision making approaches based on interval-valued hesitant fuzzy graphs. Firstly, the related notion of interval-valued hesitant fuzzy graphs is established from the aspect of definitions, operation rules and mapping relationships. Based on the constructed notion, an approach to interval-valued hesitant fuzzy graphs in multi-attribute decision making with correlations and prioritization relationships is proposed. At last, a case study along with a comparative analysis is given to illustrate the feasibility and efficiency of the proposed multi-attribute decision making approach. Compared with classical interval-valued hesitant fuzzy multi-attribute decision making approaches, the results show that the proposed approach could reasonably solve interval-valued hesitant fuzzy multi-attribute decision making problems that are characterized by correlations and prioritization relationships between attributes at the same time.

       

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