Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment
Resilient suppliers can reduce supply chain risk, effectively avoid supply chain disruption, and bring profits to enterprises. However, there is no united measuring index system to evaluate the resilient supplier under supply chain environment, and the assessment language sets are usually crisp valu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2019/2456260 |
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| _version_ | 1832560909769244672 |
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| author | Jiawu Gan Shuqi Zhong Sen Liu Dan Yang |
| author_facet | Jiawu Gan Shuqi Zhong Sen Liu Dan Yang |
| author_sort | Jiawu Gan |
| collection | DOAJ |
| description | Resilient suppliers can reduce supply chain risk, effectively avoid supply chain disruption, and bring profits to enterprises. However, there is no united measuring index system to evaluate the resilient supplier under supply chain environment, and the assessment language sets are usually crisp values. Therefore, in order to fill the research gap, this paper proposes a hybrid method, which combines triangular fuzzy number, the best-worst method (BWM), and the modular TOPSIS in random environments for group decision-making (GMo-RTOPSIS) to solve the above problem. Firstly, the weight of decision-maker is calculated by using fuzzy BWM which can deal with triangular fuzzy numbers. Secondly, triangular fuzzy number is introduced into GMo-RTOPSIS, and combined with fuzzy BWM, alternatives are sorted to select the best resilient supply chain partner. Finally, the feasibility and universality of this method are proved by illustrative examples. |
| format | Article |
| id | doaj-art-e65a525619d44e5a8ac1fd4f4a7543f9 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-e65a525619d44e5a8ac1fd4f4a7543f92025-02-03T01:26:30ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2019-01-01201910.1155/2019/24562602456260Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain EnvironmentJiawu Gan0Shuqi Zhong1Sen Liu2Dan Yang3International Business School, Yunnan University of Finance and Economics, Kunming 650221, ChinaInternational Business School, Yunnan University of Finance and Economics, Kunming 650221, ChinaSchool of Logistics, Yunnan University of Finance and Economics, Kunming 650221, ChinaInternational Business School, Yunnan University of Finance and Economics, Kunming 650221, ChinaResilient suppliers can reduce supply chain risk, effectively avoid supply chain disruption, and bring profits to enterprises. However, there is no united measuring index system to evaluate the resilient supplier under supply chain environment, and the assessment language sets are usually crisp values. Therefore, in order to fill the research gap, this paper proposes a hybrid method, which combines triangular fuzzy number, the best-worst method (BWM), and the modular TOPSIS in random environments for group decision-making (GMo-RTOPSIS) to solve the above problem. Firstly, the weight of decision-maker is calculated by using fuzzy BWM which can deal with triangular fuzzy numbers. Secondly, triangular fuzzy number is introduced into GMo-RTOPSIS, and combined with fuzzy BWM, alternatives are sorted to select the best resilient supply chain partner. Finally, the feasibility and universality of this method are proved by illustrative examples.http://dx.doi.org/10.1155/2019/2456260 |
| spellingShingle | Jiawu Gan Shuqi Zhong Sen Liu Dan Yang Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment Discrete Dynamics in Nature and Society |
| title | Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment |
| title_full | Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment |
| title_fullStr | Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment |
| title_full_unstemmed | Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment |
| title_short | Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment |
| title_sort | resilient supplier selection based on fuzzy bwm and gmo rtopsis under supply chain environment |
| url | http://dx.doi.org/10.1155/2019/2456260 |
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