Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information
The aim of this study is to develop a new closeness degree-based hesitant trapezoidal fuzzy (HTrF) multicriteria decision making (MCDM) approach for identifying the most appropriate green suppliers in food supply chain involving uncertain qualitative evaluation information. The uniqueness of the pro...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2018/3178039 |
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| _version_ | 1849307457998815232 |
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| author | Xiaolu Zhang Touping Yang Wei Liang Meifang Xiong |
| author_facet | Xiaolu Zhang Touping Yang Wei Liang Meifang Xiong |
| author_sort | Xiaolu Zhang |
| collection | DOAJ |
| description | The aim of this study is to develop a new closeness degree-based hesitant trapezoidal fuzzy (HTrF) multicriteria decision making (MCDM) approach for identifying the most appropriate green suppliers in food supply chain involving uncertain qualitative evaluation information. The uniqueness of the proposed HTrF MCDM method is the consideration of uncertain qualitative information represented by flexible linguistic expressions based on HTrF values and the construction of compromise solution with the revised closeness degree. The revised closeness degree can make sure that the most appropriate solution has the shortest distance from the HTrF positive ideal solution and the farthest distance from the HTrF negative ideal solution, simultaneously. This proposed HTrF MCDM technique not only offers a simple and efficient decision support tool to aid the food firms for identifying the optimal suppliers in food supply chain but also can enable the managers of food firms to better understand the complete evaluation and decision processes. In addition, this study provides a novel defuzzification technique to manage the HTrF weights values of main-criteria and subcriteria, respectively. |
| format | Article |
| id | doaj-art-213f08265c2e4fbba6e54821656bc044 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-213f08265c2e4fbba6e54821656bc0442025-08-20T03:54:47ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2018-01-01201810.1155/2018/31780393178039Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative InformationXiaolu Zhang0Touping Yang1Wei Liang2Meifang Xiong3The Collaborative Innovation Center, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaThe Collaborative Innovation Center, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaThe Collaborative Innovation Center, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaCollege of Modern Economics & Management, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaThe aim of this study is to develop a new closeness degree-based hesitant trapezoidal fuzzy (HTrF) multicriteria decision making (MCDM) approach for identifying the most appropriate green suppliers in food supply chain involving uncertain qualitative evaluation information. The uniqueness of the proposed HTrF MCDM method is the consideration of uncertain qualitative information represented by flexible linguistic expressions based on HTrF values and the construction of compromise solution with the revised closeness degree. The revised closeness degree can make sure that the most appropriate solution has the shortest distance from the HTrF positive ideal solution and the farthest distance from the HTrF negative ideal solution, simultaneously. This proposed HTrF MCDM technique not only offers a simple and efficient decision support tool to aid the food firms for identifying the optimal suppliers in food supply chain but also can enable the managers of food firms to better understand the complete evaluation and decision processes. In addition, this study provides a novel defuzzification technique to manage the HTrF weights values of main-criteria and subcriteria, respectively.http://dx.doi.org/10.1155/2018/3178039 |
| spellingShingle | Xiaolu Zhang Touping Yang Wei Liang Meifang Xiong Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information Discrete Dynamics in Nature and Society |
| title | Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information |
| title_full | Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information |
| title_fullStr | Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information |
| title_full_unstemmed | Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information |
| title_short | Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information |
| title_sort | closeness degree based hesitant trapezoidal fuzzy multicriteria decision making method for evaluating green suppliers with qualitative information |
| url | http://dx.doi.org/10.1155/2018/3178039 |
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