Evaluation and selection of sustainable suppliers in supply chain using new GP-DEA model with imprecise data

Subject Areas : Mathematical Optimization

Saeid Jafarzadeh Ghoushchi ¹ , Mehran Dodkanloi Milan ² , Mustafa Jahangoshai Rezaee ³

1 - Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran
2 - Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran
3 - Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran

Received: 2020-10-07 Accepted : 2020-10-07 Published : 2018-09-01

Keywords: Sustainable supplier selection , Environmental  Economic and social performance , Imprecise data envelopment analysis  Goal programming,

Abstract :

Nowadays, with respect to knowledge growth about enterprise sustainability, sustainable supplier selection is considered a vital factor in sustainable supply chain management. On the other hand, usually in real problems, the data are imprecise. One method that is helpful for the evaluation and selection of the sustainable supplier and has the ability to use a variety of data types is data envelopment analysis (DEA). In the present article, first, the supplier efficiency is measured with respect to all economic, social and environmental dimensions using DEA and applying imprecise data. Then, to have a general evaluation of the suppliers, the DEA model is developed using imprecise data based on goal programming (GP). Integrating the set of criteria changes the new model into a coherent framework for sustainable supplier selection. Moreover, employing this model in a multilateral sustainable supplier selection can be an incentive for the suppliers to move towards environmental, social and economic activities. Improving environmental, economic and social performance will mean improving the supply chain performance. Finally, the application of the proposed approach is presented with a real dataset.