A Fuzzy TOPSIS Model to Rank Automotive Suppliers

This paper highlights the most significant criteria and sub-criteria in automotive industries for selecting the best supplier from the previous paper. Supplier selection process is one of the key activities of management in a supply chain environment. This paper presents another methodology to selec...

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Main Authors: Amir, Azizi, Aikhuele, Daniel O., Souleman, Fathi S.
Format: Article
Language:English
Published: Elsevier Ltd 2015
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/11115/1/A%20Fuzzy%20TOPSIS%20Model%20to%20Rank%20Automotive%20Suppliers.pdf
http://umpir.ump.edu.my/id/eprint/11115/
http://dx.doi.org/10.1016/j.promfg.2015.07.028
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spelling my.ump.umpir.111152018-02-23T02:35:27Z http://umpir.ump.edu.my/id/eprint/11115/ A Fuzzy TOPSIS Model to Rank Automotive Suppliers Amir, Azizi Aikhuele, Daniel O. Souleman, Fathi S. TS Manufactures This paper highlights the most significant criteria and sub-criteria in automotive industries for selecting the best supplier from the previous paper. Supplier selection process is one of the key activities of management in a supply chain environment. This paper presents another methodology to select the most suitable supplier in a supply chain system using Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS). Triangular Fuzzy set is applied into the proposed model to handle the vagueness. The interdependencies between criteria are considered. In our FTOPSIS model, the results show that FTOPSIS is remarkably successful in determining the best supplier with stability in the ranking as it relates to the different criteria weights and multiple sub-criteria. The proposed methodology presents a comprehensive multi-criteria approach to find the best ranking among the alternative suppliers. The result shows that supplier A is the best supplier with the Closeness Coefficient of 0.5407. The FTOPSIS model proposed can be apply on other vague multiple criteria decision making problem since it shows good result in the research. Future research may expand the work to another field of study or in a different type of industry. Elsevier Ltd 2015 Article PeerReviewed application/pdf en cc_by_nc_nd http://umpir.ump.edu.my/id/eprint/11115/1/A%20Fuzzy%20TOPSIS%20Model%20to%20Rank%20Automotive%20Suppliers.pdf Amir, Azizi and Aikhuele, Daniel O. and Souleman, Fathi S. (2015) A Fuzzy TOPSIS Model to Rank Automotive Suppliers. Procedia Manufacturing, 2. pp. 159-164. ISSN 2351-9789 http://dx.doi.org/10.1016/j.promfg.2015.07.028 doi:10.1016/j.promfg.2015.07.028
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TS Manufactures
spellingShingle TS Manufactures
Amir, Azizi
Aikhuele, Daniel O.
Souleman, Fathi S.
A Fuzzy TOPSIS Model to Rank Automotive Suppliers
description This paper highlights the most significant criteria and sub-criteria in automotive industries for selecting the best supplier from the previous paper. Supplier selection process is one of the key activities of management in a supply chain environment. This paper presents another methodology to select the most suitable supplier in a supply chain system using Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS). Triangular Fuzzy set is applied into the proposed model to handle the vagueness. The interdependencies between criteria are considered. In our FTOPSIS model, the results show that FTOPSIS is remarkably successful in determining the best supplier with stability in the ranking as it relates to the different criteria weights and multiple sub-criteria. The proposed methodology presents a comprehensive multi-criteria approach to find the best ranking among the alternative suppliers. The result shows that supplier A is the best supplier with the Closeness Coefficient of 0.5407. The FTOPSIS model proposed can be apply on other vague multiple criteria decision making problem since it shows good result in the research. Future research may expand the work to another field of study or in a different type of industry.
format Article
author Amir, Azizi
Aikhuele, Daniel O.
Souleman, Fathi S.
author_facet Amir, Azizi
Aikhuele, Daniel O.
Souleman, Fathi S.
author_sort Amir, Azizi
title A Fuzzy TOPSIS Model to Rank Automotive Suppliers
title_short A Fuzzy TOPSIS Model to Rank Automotive Suppliers
title_full A Fuzzy TOPSIS Model to Rank Automotive Suppliers
title_fullStr A Fuzzy TOPSIS Model to Rank Automotive Suppliers
title_full_unstemmed A Fuzzy TOPSIS Model to Rank Automotive Suppliers
title_sort fuzzy topsis model to rank automotive suppliers
publisher Elsevier Ltd
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/11115/1/A%20Fuzzy%20TOPSIS%20Model%20to%20Rank%20Automotive%20Suppliers.pdf
http://umpir.ump.edu.my/id/eprint/11115/
http://dx.doi.org/10.1016/j.promfg.2015.07.028
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score 13.159267