Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making model
The quality performance of power equipment suppliers is directly related to the stable and safe operation of the grid. This study presents a decision-making model based on q-rung orthopair fuzzy sets (q-ROFS) to evaluate suppliers, focusing on quality as the key criterion. To assess the objectivity...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-11-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024164213 |
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| author | Jiawei Mao JinGuo Huang Jing Liu Chao Peng ShiZe Zhang |
| author_facet | Jiawei Mao JinGuo Huang Jing Liu Chao Peng ShiZe Zhang |
| author_sort | Jiawei Mao |
| collection | DOAJ |
| description | The quality performance of power equipment suppliers is directly related to the stable and safe operation of the grid. This study presents a decision-making model based on q-rung orthopair fuzzy sets (q-ROFS) to evaluate suppliers, focusing on quality as the key criterion. To assess the objectivity and comprehensiveness of the results, we provide an innovative information fusion method that integrates the four dimensions of supply risk, supplier quality capability, profit impact, and willingness into the decision-making process. Considering the uncertainty and inconsistency in the decision-making process, in the weight determination stage, the q-ROFS-FWZIC method is used as the standard to allocate weights accurately. In the ranking stage, the q-ROFS-MABAC method was constructed to improve the consistency of evaluation results, and suppliers were ranked based on summarized performance data. A real-world case study involving power transformer suppliers illustrates the effectiveness of the proposed model. This research offers valuable insights for decision-makers in the power sector to optimize supplier selection, improve quality control measures, and ensure the ongoing reliability of the grid. Furthermore, this method can also be extended to other fields to solve various MCDM problems. |
| format | Article |
| id | doaj-art-1e1950c5bcd14d74b13c383f4d9f5777 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-1e1950c5bcd14d74b13c383f4d9f57772024-11-30T07:12:47ZengElsevierHeliyon2405-84402024-11-011022e40390Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making modelJiawei Mao0JinGuo Huang1Jing Liu2Chao Peng3ShiZe Zhang4School of Mechanical Science and Engineering, Huazhong University of Science and Technology, No. 1037, Juy Road, Hongshan District, Wuhan, 430074, ChinaSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, No. 1037, Juy Road, Hongshan District, Wuhan, 430074, ChinaSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, No. 1037, Juy Road, Hongshan District, Wuhan, 430074, China; Corresponding author.China Electrical Power Research Institute, Wuhan, Hubei, 430074, ChinaChina Electrical Power Research Institute, Wuhan, Hubei, 430074, ChinaThe quality performance of power equipment suppliers is directly related to the stable and safe operation of the grid. This study presents a decision-making model based on q-rung orthopair fuzzy sets (q-ROFS) to evaluate suppliers, focusing on quality as the key criterion. To assess the objectivity and comprehensiveness of the results, we provide an innovative information fusion method that integrates the four dimensions of supply risk, supplier quality capability, profit impact, and willingness into the decision-making process. Considering the uncertainty and inconsistency in the decision-making process, in the weight determination stage, the q-ROFS-FWZIC method is used as the standard to allocate weights accurately. In the ranking stage, the q-ROFS-MABAC method was constructed to improve the consistency of evaluation results, and suppliers were ranked based on summarized performance data. A real-world case study involving power transformer suppliers illustrates the effectiveness of the proposed model. This research offers valuable insights for decision-makers in the power sector to optimize supplier selection, improve quality control measures, and ensure the ongoing reliability of the grid. Furthermore, this method can also be extended to other fields to solve various MCDM problems.http://www.sciencedirect.com/science/article/pii/S2405844024164213Power equipmentDecision supportMCDMQ-rung orthopair fuzzy set |
| spellingShingle | Jiawei Mao JinGuo Huang Jing Liu Chao Peng ShiZe Zhang Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making model Heliyon Power equipment Decision support MCDM Q-rung orthopair fuzzy set |
| title | Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making model |
| title_full | Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making model |
| title_fullStr | Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making model |
| title_full_unstemmed | Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making model |
| title_short | Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making model |
| title_sort | power equipment supplier evaluation under a q rung orthopair fuzzy set based decision making model |
| topic | Power equipment Decision support MCDM Q-rung orthopair fuzzy set |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024164213 |
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