Proceedings of the 2017 International Conference on Humanities Science, Management and Education Technology (HSMET 2017)

Application of Entropy-AHP-TOPSIS methods to Select Food Suppliers

Authors
Yanan Wang, Mengyao Shi, Haitao Liu
Corresponding Author
Yanan Wang
Available Online February 2017.
DOI
10.2991/hsmet-17.2017.39How to use a DOI?
Keywords
Food supplier, index system, AHP, entropy, TOPSIS
Abstract

In this paper, we give a framework to select food suppliers. The proposed framework is divided into three stages. During the first stage, we construct an index system that include quality, ability, management, service and R&D. In the second stage, we use entropy and Analytic Hierarchy Process(AHP) to determine weights. The third stage is associated with the application of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank food suppliers and select the best one. In the end, we give an example to prove the mothod is validity and fessibility.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Humanities Science, Management and Education Technology (HSMET 2017)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
February 2017
ISBN
10.2991/hsmet-17.2017.39
ISSN
2352-5398
DOI
10.2991/hsmet-17.2017.39How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yanan Wang
AU  - Mengyao Shi
AU  - Haitao Liu
PY  - 2017/02
DA  - 2017/02
TI  - Application of Entropy-AHP-TOPSIS methods to Select Food Suppliers
BT  - Proceedings of the 2017 International Conference on Humanities Science, Management and Education Technology (HSMET 2017)
PB  - Atlantis Press
SP  - 191
EP  - 196
SN  - 2352-5398
UR  - https://doi.org/10.2991/hsmet-17.2017.39
DO  - 10.2991/hsmet-17.2017.39
ID  - Wang2017/02
ER  -