Supplier selection for managing supply risks in supply chain: a fuzzy approach

Paul, SK

Supplier selection for managing supply risks in supply chain: a fuzzy approach

Paul, SK

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Publication Type:: Journal Article
Citation:: International Journal of Advanced Manufacturing Technology, 2015, 79 (1-4), pp. 657 - 664
Issue Date:: 2015-07-28

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Field	Value	Language
dc.contributor.author	Paul, SK https://orcid.org/0000-0001-9523-179X	en_US
dc.date.issued	2015-07-28	en_US
dc.identifier.citation	International Journal of Advanced Manufacturing Technology, 2015, 79 (1-4), pp. 657 - 664	en_US
dc.identifier.issn	0268-3768	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119255
dc.description.abstract	© 2015, Springer-Verlag London. Supplier selection is one of the most important tasks for supply chain decision making, and there are many quantitative and qualitative factors that affect this process. This paper develops a simple and user-friendly supplier selection process for a supply chain which considers various selection criteria for managing supply risks. A rule-based fuzzy inference system (FIS) model is developed using the fuzzy logic toolbox in MATLAB R2012a to select the most excellent supplier by considering both quantitative and qualitative selection criteria. We identify a total of 18 selection criteria, of which four are quantitative and 14 qualitative. Risk factors are also incorporated in the model by developing fuzzy input and output criteria, and the best supplier is selected based on the aggregated supplier ranking index value. Finally, a numerical example presented to explain the usefulness of the developed model.	en_US
dc.relation.ispartof	International Journal of Advanced Manufacturing Technology	en_US
dc.relation.isbasedon	10.1007/s00170-015-6867-y	en_US
dc.subject.classification	Industrial Engineering & Automation	en_US
dc.title	Supplier selection for managing supply risks in supply chain: a fuzzy approach	en_US
dc.type	Journal Article
utslib.citation.volume	1-4	en_US
utslib.citation.volume	79	en_US
utslib.for	091099 Manufacturing Engineering not elsewhere classified	en_US
utslib.for	089999 Information and Computing Sciences not elsewhere classified	en_US
utslib.for	010206 Operations Research	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Management Discipline
utslib.copyright.status	closed_access
pubs.issue	1-4	en_US
pubs.publication-status	Published	en_US
pubs.volume	79	en_US

Abstract:

© 2015, Springer-Verlag London. Supplier selection is one of the most important tasks for supply chain decision making, and there are many quantitative and qualitative factors that affect this process. This paper develops a simple and user-friendly supplier selection process for a supply chain which considers various selection criteria for managing supply risks. A rule-based fuzzy inference system (FIS) model is developed using the fuzzy logic toolbox in MATLAB R2012a to select the most excellent supplier by considering both quantitative and qualitative selection criteria. We identify a total of 18 selection criteria, of which four are quantitative and 14 qualitative. Risk factors are also incorporated in the model by developing fuzzy input and output criteria, and the best supplier is selected based on the aggregated supplier ranking index value. Finally, a numerical example presented to explain the usefulness of the developed model.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/119255