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Mathematical Problems in Engineering
Volume 2016, Article ID 8475987, 17 pages
Research Article

A New Methodology of Multicriteria Decision-Making in Supplier Selection Based on -Numbers

1School of Computer and Information Sciences, Southwest University, Chongqing 400715, China
2Big Data Decision Institute, Jinan University, Tianhe, Guangzhou 510632, China
3School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, China

Received 14 October 2015; Revised 27 November 2015; Accepted 29 November 2015

Academic Editor: Young Hae Lee

Copyright © 2016 Bingyi Kang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Supplier selection is a significant issue of multicriteria decision-making (MCDM), which has been heavily studied with classical fuzzy methodologies, but the reliability of the knowledge from domain experts is not efficiently taken into consideration. -number introduced by Zadeh has more power to describe the knowledge of human being with uncertain information considering both restraint and reliability. In this paper, a methodology for supplier selection using -numbers is proposed considering information transformation. It includes two parts: one solves the issue of how to convert -number to the classic fuzzy number according to the fuzzy expectation; the other solves the problem of how to get the optimal priority weight for supplier selection with genetic algorithm (GA), which is an efficient and flexible method for calculating the priority weight of the judgement matrix. Finally, an example for supplier selection is used to illustrate the effectiveness the proposed methodology.