A Green Supplier Assessment Method for Manufacturing Enterprises Based on Rough ANP and Evidence Theory

被引:6
|
作者
Li, Lianhui [1 ]
Wang, Hongguang [2 ]
机构
[1] North Minzu Univ, Coll Mechatron Engn, Yinchuan 750021, Peoples R China
[2] 713th Res Inst China Shipbldg Ind Corp, Zhengzhou 450052, Henan, Peoples R China
来源
INFORMATION | 2018年 / 9卷 / 07期
关键词
green supplier; rough ANP; trapezoidal fuzzy number; rough boundary interval; evidence theory; trust interval;
D O I
10.3390/info9070162
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Within the context of increasingly serious global environmental problems, green supplier assessment has become one of the key links in modern green supply chain management. In the actual work of green supplier assessment, the information of potential suppliers is often ambiguous or even absent, and there are interrelationships and feedback-like effects among assessment indexes. Additionally, the thinking of experts in index importance judgment is always ambiguous and subjective. To handle the uncertainty and incompleteness in green supplier assessment, we propose a green supplier assessment method based on rough ANP and evidence theory. The uncertain index value is processed by membership degree. Trapezoidal fuzzy number is adopted to express experts' judgment on the relative importance of the indexes, and rough boundary interval is used to integrate the judgment opinions of multiple experts. The ANP structure is built to deal with the interrelationship and feedback-like effects among indexes. Then, the index weight is calculated by ANP method. Finally, the green suppliers are assessed by a trust interval, based on evidence theory. The feasibility and effectiveness of the proposed method is verified by an application of a bearing cage supplier assessment.
引用
收藏
页数:18
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