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Vendor selection and uncertainty

Authors: Rakesh Verma; Saroj Koul; Kannan Govindan 0002;

Vendor selection and uncertainty

Abstract

Vendor selection is of strategic importance in any industry. This paper uses fuzzy tools for vendor selection to improve decision-making through a more systematic and logical approach. Expert opinion is portrayed by allocating different fuzzy weights to the linguistic data in the form of triangular fuzzy numbers (TFN). The scores are evaluated using fuzzy arithmetic operations and the index of optimism is used to evaluate the vendors. Also, to bring in consistency in the evaluation, results are compared with the fuzzy technique for order preference by similarity to an ideal solution (TOPSIS), another well known multicriteria decision-making (MCDM) approach affected by uncertainty. This concept, if adopted, can be used for any industry where vendor selection is based on a set criteria and linguistic judgement variables.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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