运筹与管理 ›› 2018, Vol. 27 ›› Issue (1): 125-131.DOI: 10.12005/orms.2018.0019

• 应用研究 • 上一篇    下一篇

区间直觉模糊信息下的监理工程师信用评价

赵丽丽1,2, 王雪青1, 陈超3   

  1. 1.天津大学 管理与经济学部,天津 300072;
    2.河北经贸大学 管理科学与工程学院,河北 石家庄 050061;
    3.天津地铁资源投资有限公司 发展策划部,天津 300102
  • 收稿日期:2014-01-27 出版日期:2018-01-25
  • 作者简介:赵丽丽(1985-),女,讲师,研究方向为工程项目决策与控制、信用治理;王雪青(1965-),女,博士生导师,教授,主要研究方向为工程项目管理、建筑市场信用;陈超(1984-),男,硕士研究生,研究方向为预测与决策。
  • 基金资助:
    国家自然科学基金资助项目(71172148);国家火炬计划重大项目(2015GH720202);河北省社会科学基金项目(HB17GL052)

Credit Evaluation of Supervision Engineers with Interval-valued Intuitionistic Fuzzy Information

ZHAO Li-li1,2, WANG Xue-qing1, CHEN Chao3   

  1. 1.College of Management and Economics, Tianjin University, Tianjin 300072, China;
    2.Hebei University of Economics and Business, Shijiazhuang 050061, China;
    3.Ministry of Development Plan, Tianjin Metro Resource TPG Capital, Tianjin 300102, China
  • Received:2014-01-27 Online:2018-01-25

摘要: 由于外界环境的复杂多变和决策者的主观偏好,若运用传统信用评价方法单从业主或承包商的视角对监理工程师进行信用评价,会导致评价结果出现偏差。针对此本文从利益相关者的层面,运用区间直觉模糊集构建模糊综合评价模型,对监理工程师的信用行为进行评价,此模型通过相似性度量值、精确度函数分别得到利益相关者的权重和信用评价指标的权重,并在此基础上运用IIFHG等算子对区间直觉模糊信息进行集结,可以充分考虑不同利益相关者在评价过程中的话语权,有效规避评价主体因主观偏好所引起的偏差。最后通过算例分析表明该方法的有效性和合理性。

关键词: 区间直觉模糊集, 相似性度量值, 信用评价, 利益相关者

Abstract: Traditional credit evaluation methods only evaluate from the perspective of the owner or contractor. Because the supervision engineers’ information is uncertain and evaluation subjects are inherently subjective, evaluation information can’t be accurately expressed with precise real number. Therefore, from the stakeholders’ perspective, interval-valued intuitionistic fuzzy sets are used to evaluate the credit of supervision engineers comprehensively. The method obtains the weights of stakeholders with similarity measure, which establishes a linear programming model based on accuracy function to determine the weights of evaluation index. Then we use IIFHG and IIFWG operator to fuse the interval-valued intuitionistic fuzzy information. The method can fully reflect the differences of different credit indicators, avert the declination caused by the the subjectivity of the subject. Finally, a numerical example shows the effectiveness and rationality.

Key words: interval-valued intuitionistic fuzzy sets, similarity measure, credit evaluation, stakeholder

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