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Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry.

Authors :
Jain, Vipul
Sangaiah, Arun Kumar
Sakhuja, Sumit
Thoduka, Nittin
Aggarwal, Rahul
Source :
Neural Computing & Applications. Apr2018, Vol. 29 Issue 7, p555-564. 10p.
Publication Year :
2018

Abstract

Supplier selection is one of the key activities of purchase management in supply chain. Supplier selection is a multifaceted problem relating qualitative and quantitative multi-criteria. This paper deals with a supplier selection problem in an Indian automobile company. The work presents selection of headlamp supplier using integrated fuzzy multi-criteria decision-making approaches: analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). The selection process starts with identifying the criteria based on literature review and interviewing industry experts. Weights to criteria are assigned using AHP, and suppliers are ranked using AHP and TOPSIS. Consistency tests are carried out to check the quality of expert’s inputs. Also, sensitivity analysis is done to check the robustness of the approach. The results address that fuzzy approaches could be effective and more accurate than the existing approaches for supplier selection problems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09410643
Volume :
29
Issue :
7
Database :
Academic Search Index
Journal :
Neural Computing & Applications
Publication Type :
Academic Journal
Accession number :
128548179
Full Text :
https://doi.org/10.1007/s00521-016-2533-z