Supplier selection based on evidence theory and analytic network process

Xiaoge Zhang; Yong Deng; Felix T.S. Chan; Andrew Adamatzky; Sankaran Mahadevan

doi:10.1177/0954405414551105

Supplier selection based on evidence theory and analytic network process

Xiaoge Zhang, Yong Deng (Corresponding Author), Felix T.S. Chan, Andrew Adamatzky, Sankaran Mahadevan

Research output: Journal article publication › Journal article › Academic research › peer-review

63 Citations (Scopus)

Abstract

The supplier selection is a key component of the supply chain management. Existing methods for the supplier selection are based on analytic network process. They can handle the interdependence of decision attributes; however, these methods could not guarantee an optimal solution when given vague or incomplete input data. To deal with the uncertainties of input data, we propose methods combining analytic network process with Dempster'Shafer evidence theory. We demonstrate efficiency and accuracy of the proposed method in a numerical example. We demonstrate that the proposed method is flexible and effective in dealing with the supplier selection problem.

Original language	English
Pages (from-to)	562-573
Number of pages	12
Journal	Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
Volume	230
Issue number	3
DOIs	https://doi.org/10.1177/0954405414551105
Publication status	Published - Mar 2016

Keywords

Analytical network process
Dempster'Shafer evidence theory
Dempster'Shafer/analytic network process
Supplier selection

ASJC Scopus subject areas

Mechanical Engineering
Industrial and Manufacturing Engineering

More information

10.1177/0954405414551105

http://hdl.handle.net/10397/104573

Cite this

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title = "Supplier selection based on evidence theory and analytic network process",

abstract = "The supplier selection is a key component of the supply chain management. Existing methods for the supplier selection are based on analytic network process. They can handle the interdependence of decision attributes; however, these methods could not guarantee an optimal solution when given vague or incomplete input data. To deal with the uncertainties of input data, we propose methods combining analytic network process with Dempster'Shafer evidence theory. We demonstrate efficiency and accuracy of the proposed method in a numerical example. We demonstrate that the proposed method is flexible and effective in dealing with the supplier selection problem.",

keywords = "Analytical network process, Dempster'Shafer evidence theory, Dempster'Shafer/analytic network process, Supplier selection",

author = "Xiaoge Zhang and Yong Deng and Chan, {Felix T.S.} and Andrew Adamatzky and Sankaran Mahadevan",

note = "Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work is partially supported by National Natural Science Foundation of China (grant no. 61174022); RandD Program of China (2012BAH07B01); National High Technology Research and Development Program of China (863 Program) (grant no. 2013AA013801); Science and Technology Planning Project of Guangdong Province, China (grant nos 2010B010600034, 2012B091100192); Business Intelligence Key Team of Guangdong University of Foreign Studies (grant no. TD1202) and the open funding project of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University (grant no. BUAA-VR-14KF-02). Publisher Copyright: {\textcopyright} IMechE 2014.",

year = "2016",

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doi = "10.1177/0954405414551105",

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Supplier selection based on evidence theory and analytic network process. / Zhang, Xiaoge; Deng, Yong (Corresponding Author); Chan, Felix T.S. et al.
In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 230, No. 3, 03.2016, p. 562-573.

Research output: Journal article publication › Journal article › Academic research › peer-review

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Supplier selection based on evidence theory and analytic network process

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Keywords

ASJC Scopus subject areas

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