Supplier selection using axiomatic fuzzy set and TOPSIS methodology in supply chain management

被引:37
|
作者
Li, Ye [1 ,2 ]
Liu, Xiaodong [1 ,2 ]
Chen, Yan [1 ]
机构
[1] Dalian Maritime Univ, Transportat Management Coll, Dalian 116026, Peoples R China
[2] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian 116024, Peoples R China
基金
中国博士后科学基金;
关键词
Fuzzy analytic hierarchy process; Qualitative and qualitative criteria; Technique for order preference by similarity to ideal solution; Axiomatic fuzzy set; Supplier selection; LOGIC OPERATIONS; MODEL; AHP; REPRESENTATIONS; OPPORTUNITIES; EXTENSION; FRAMEWORK; BENEFITS; COSTS; RISK;
D O I
10.1007/s10700-012-9117-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The current paper presents a comprehensive methodology for supplier selection. In the first stage, the linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the criteria. The Axiomatic Fuzzy Set clustering (AFS) method, which handles ambiguity and fuzziness in the supplier selection problem effectively, is applied to cluster the suppliers and evaluate each potential supplier that aims at obtaining initial supplier ranking. In the second stage, the Fuzzy Analytic Hierarchy Process (FAHP) model is constructed to determine the weight of various quantitative and qualitative criteria. To address multiple decision criteria in supplier ranking, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to select the final suppliers. A numerical example composed of 30 suppliers and 6 criteria is studied, and the experimental results show that the proposed evaluation framework is suitable for supplier selection decisions even with the dependent criteria/attributes.
引用
收藏
页码:147 / 176
页数:30
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