运筹与管理 ›› 2016, Vol. 25 ›› Issue (3): 125-131.DOI: 10.12005/orms.2016.0092

• 理论分析与方法探讨 • 上一篇    下一篇

考虑可信度和属性优先级的犹豫模糊决策方法

阮传扬1,2,杨建辉1,韩莉娜3,刘若冰1   

  1. 1.华南理工大学 工商管理学院,广东 广州 510640;
    2.佛山科学技术学院 经济管理与法学院,广东 广州 528000;3.华南理工大学 经济贸易学院,广东 广州 510006
  • 收稿日期:2014-07-08 出版日期:2016-06-25
  • 作者简介:阮传扬(1987-),男,河南周口人,博士研究生,研究方向为管理决策与信息融合;杨建辉(1960-),男,贵州黔东南苗族侗族自治州人,教授,博导,博士后,研究方向为智能决策与金融风险管理。
  • 基金资助:
    国家自然科学基金资助项目(71073056);广东省政府重点项目(N6131810);中央高校基本科研业务资助项目(Y6090020)

Hesitant Fuzzy Decision Making Method with Confidence Levels and Preference Relations on Attributes

RUAN Chuan-yang1,2, YANG Jian-hui1, HAN Li-na3, LIU Ruo-bing1   

  1. 1.School of Business Administration, South China University of Technology, Guangzhou 510640, China;
    2.School of Business and Law, Foshan University, Foshan 528000, China;
    3.School of Economic and Commerce, South China University of Technology, Guangzhou 510006, China
  • Received:2014-07-08 Online:2016-06-25

摘要: 研究了考虑可信度的犹豫模糊混合集成因子以及考虑属性优先级的犹豫模糊多属性决策方法。首先给出了用于衡量数据差异程度的加权变异率公式,并证明了其具有类似于基尼系数的优良度量性质,之后在此基础上提出了可信度诱导犹豫模糊混合平均(CIHFHA)算子。针对属性权重信息未知的犹豫模糊决策问题,构建了一种新的考虑属性优先级的熵值修正G1的组合赋权方法,该方法可有效地利用属性客观评价数据以及通过考虑属性优先级体现专家意见,解决了主客观权重分配问题,得出的属性权重更加客观、合理。之后给出了一种基于CIHFHA算子和组合赋权方法的多属性决策方法,算例说明该方法的有效性和实用性。

关键词: 模糊决策, 犹豫模糊集, 加权变异率, 熵值修正G1

Abstract: The multiple attribute decision making problem with confidence levels and preference information on attributes under hesitant fuzzy environment is studied. At first, we introduce a useful formula of weighed rate of variation for measuring data variation degree and shows the index of weighed rate of variation has good measuring characteristics like Gini coefficient. Then we put forward confidence induced hesitant fuzzy hybrid averaging(CIHFHA)operator based on the weighed rate of variation. According to the hesitant fuzzy multi-attribute decision making problem of unknown attribute weights information, we construct a new evaluation model of attributes weights called entropy correction group G1 combination weights with preference information on attributes. The method can effectively use the objective data of attributes and reflect the opinions of experts by considering the preference information on attributes. It also settles the allocation problem of subjective and objective determination problem, and makes the obtained attribute weights more objective and reasonable. Finally, a hesitant fuzzy multiple attribute decision making method based on CIHFHA operator and combination weights method is provided, and examples are given to illustrate the validity and practicability of the method.

Key words: fuzzy decision-making, hesitant fuzzy sets, weighed rate of variation, entropy correction group G1

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