A Fuzzy Multi-Objective Mathematical Model for Supplier Evaluation in a Reliable Supply Chain considering Different Risk Levels
One of the advantages of sustainable competition for manufacturing systems is to make supply chain activities more efficient and effective. One of the major parts of these activities that can save a lot of costs is careful outsourcing. In this study, an approach based on decision-making policies in...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2022/5852330 |
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| author | Yuanyuan Tian Saeed Bahrami null Farshad kaveh |
| author_facet | Yuanyuan Tian Saeed Bahrami null Farshad kaveh |
| author_sort | Yuanyuan Tian |
| collection | DOAJ |
| description | One of the advantages of sustainable competition for manufacturing systems is to make supply chain activities more efficient and effective. One of the major parts of these activities that can save a lot of costs is careful outsourcing. In this study, an approach based on decision-making policies in order to select suppliers and allocate order volume to them is introduced. The main contribution of this research is a comprehensive approach for optimizing both supplier evaluation and order allocation. In this regard, first, based on the evaluation, 39 key indicators were identified to evaluate the suppliers, and based on the content analysis, 25 key indicators were screened based on the Lavache method. Next, based on the fuzzy Delphi method, 11 indicators were selected from among the 25 key effective indicators. Finally, the Best-Worst Method (BWM) and a robust multi-objective formulation are proposed to find the weight of the effective criteria and the optimal order allocation to suppliers, respectively. Moreover, it is proved that the company under study faces a variety of suppliers and there is a need to analyze key indicators such as exchange rate changes and ease of communication. Based on the BWM results, it was shown that the exchange rate change trend with a weight of 0.24 is in the first place, and the quality system support index with a weight of 0.12 is in the second place. Moreover, based on the results of the proposed robust multi-objective mathematical model, it was revealed that in order to maintain the resilience of suppliers, the total demand should be distributed among all suppliers and the second supplier with a volume of 3600 units of raw materials has the largest share in delivering the required demand. |
| format | Article |
| id | doaj-art-46456fcc78c0446b88c0586e40bbfc2a |
| institution | Kabale University |
| issn | 1607-887X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-46456fcc78c0446b88c0586e40bbfc2a2025-02-03T01:06:57ZengWileyDiscrete Dynamics in Nature and Society1607-887X2022-01-01202210.1155/2022/5852330A Fuzzy Multi-Objective Mathematical Model for Supplier Evaluation in a Reliable Supply Chain considering Different Risk LevelsYuanyuan Tian0Saeed Bahrami1null Farshad kaveh2College of Humanity and ManagementDepartment of Educational ScienceDepartment of Industrial EngineeringOne of the advantages of sustainable competition for manufacturing systems is to make supply chain activities more efficient and effective. One of the major parts of these activities that can save a lot of costs is careful outsourcing. In this study, an approach based on decision-making policies in order to select suppliers and allocate order volume to them is introduced. The main contribution of this research is a comprehensive approach for optimizing both supplier evaluation and order allocation. In this regard, first, based on the evaluation, 39 key indicators were identified to evaluate the suppliers, and based on the content analysis, 25 key indicators were screened based on the Lavache method. Next, based on the fuzzy Delphi method, 11 indicators were selected from among the 25 key effective indicators. Finally, the Best-Worst Method (BWM) and a robust multi-objective formulation are proposed to find the weight of the effective criteria and the optimal order allocation to suppliers, respectively. Moreover, it is proved that the company under study faces a variety of suppliers and there is a need to analyze key indicators such as exchange rate changes and ease of communication. Based on the BWM results, it was shown that the exchange rate change trend with a weight of 0.24 is in the first place, and the quality system support index with a weight of 0.12 is in the second place. Moreover, based on the results of the proposed robust multi-objective mathematical model, it was revealed that in order to maintain the resilience of suppliers, the total demand should be distributed among all suppliers and the second supplier with a volume of 3600 units of raw materials has the largest share in delivering the required demand.http://dx.doi.org/10.1155/2022/5852330 |
| spellingShingle | Yuanyuan Tian Saeed Bahrami null Farshad kaveh A Fuzzy Multi-Objective Mathematical Model for Supplier Evaluation in a Reliable Supply Chain considering Different Risk Levels Discrete Dynamics in Nature and Society |
| title | A Fuzzy Multi-Objective Mathematical Model for Supplier Evaluation in a Reliable Supply Chain considering Different Risk Levels |
| title_full | A Fuzzy Multi-Objective Mathematical Model for Supplier Evaluation in a Reliable Supply Chain considering Different Risk Levels |
| title_fullStr | A Fuzzy Multi-Objective Mathematical Model for Supplier Evaluation in a Reliable Supply Chain considering Different Risk Levels |
| title_full_unstemmed | A Fuzzy Multi-Objective Mathematical Model for Supplier Evaluation in a Reliable Supply Chain considering Different Risk Levels |
| title_short | A Fuzzy Multi-Objective Mathematical Model for Supplier Evaluation in a Reliable Supply Chain considering Different Risk Levels |
| title_sort | fuzzy multi objective mathematical model for supplier evaluation in a reliable supply chain considering different risk levels |
| url | http://dx.doi.org/10.1155/2022/5852330 |
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