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Vendor selection and uncertainty

Vendor selection and uncertainty 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Business Performance and Supply Chain Modelling Inderscience Publishers

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1758-9401
eISSN
1758-941X
DOI
10.1504/IJBPSCM.2009.033749
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Business Performance and Supply Chain ModellingInderscience Publishers

Published: Jan 1, 2009

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