• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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Vendors sequencing for manufacturing enterprise:
Improved TOPSIS based on SVM and trapezoidal
fuzzy number-rough set method

LI Lianhui,WANG Li,LEI Ting,DING Shaohu   

  1. (College of Mechatronic Engineering,North Minzu University,Yinchuan 750021,China)
  • Received:2016-01-15 Revised:2016-05-03 Online:2018-04-25 Published:2018-04-25

Abstract:

Considering the green connotation of manufacturing enterprise supply chain, an indicator system of vendors sequencing is established. To solve the problems such as large index number, complex calculation, and coordination difficulties, an improved TOPSIS based on SVM and trapezoidal fuzzy numberrough set method is proposed. According to the main data, a SVMbased classification model is applied for the preliminary screening of candidate vendors. Through the investigation and mastery of experts to the indicators of criteria, a trapezoidal fuzzy numberrough set method is designed to calculate the value of a vendor in the criteria by using the wisdom and experience of experts. The criteria weight is determined by CRITIC. Finally, the vendors are sequenced by the improved TOPSIS replacing Euclidean distance with relative entropy. An example of ball vendors sequencing decision of a bearing manufacturing enterprise is used to verify the practical effect of this method.

 

Key words: vendors sequencing, SVM, fuzzy number, rough set, TOPSIS