Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method
Selecting the best knitted fabric with various comfort properties is considered a complicated multi-criteria decision-making (MCDM) issue that involves ambiguity and vagueness. In such scenarios, Pythagorean fuzzy sets (PFSs) provide an effective tool for addressing uncertainty and ambiguity in MCDM...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-08-01
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| Series: | Journal of Natural Fibers |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/15440478.2023.2224124 |
| _version_ | 1827807858485362688 |
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| author | Jing Ye Ting-Yu Chen |
| author_facet | Jing Ye Ting-Yu Chen |
| author_sort | Jing Ye |
| collection | DOAJ |
| description | Selecting the best knitted fabric with various comfort properties is considered a complicated multi-criteria decision-making (MCDM) issue that involves ambiguity and vagueness. In such scenarios, Pythagorean fuzzy sets (PFSs) provide an effective tool for addressing uncertainty and ambiguity in MCDM problems that contain human subjective evaluations and judgments. First, this research identifies the factors affecting the comfort of knitted fabrics as the evaluation criteria. Second, the Bayesian best-worst method (BBWM) is preferred for less pairwise comparisons and obtains highly reliable results with a probabilistic perspective for determining the criteria weights. Furthermore, due to its logical computation approach and ease of operation, the technique for order preference by similarity to ideal solution (TOPSIS) is commonly utilized for addressing MCDM problems. Therefore, this research proposes an innovative MCDM framework that combines the BBWM technique with Pythagorean fuzzy TOPSIS (PFTOPSIS). The BBWM determines the criteria weights, and the weighted sine similarity-based PFTOPSIS is utilized to rank alternatives. The proposed BBWM-PFTOPSIS approach was employed to solve a real-world case. Moreover, this article conducts a sensitivity analysis and three comparative analyses to reveal the efficiency and reliability of the BBWM-PFTOPSIS approach. The ranking results establish the viability and effectiveness of BBWM-PFTOPSIS. |
| first_indexed | 2024-03-11T22:02:57Z |
| format | Article |
| id | doaj.art-ac3d71436e914972948f0905d594491e |
| institution | Directory Open Access Journal |
| issn | 1544-0478 1544-046X |
| language | English |
| last_indexed | 2024-03-11T22:02:57Z |
| publishDate | 2023-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Natural Fibers |
| spelling | doaj.art-ac3d71436e914972948f0905d594491e2023-09-25T10:29:01ZengTaylor & Francis GroupJournal of Natural Fibers1544-04781544-046X2023-08-0120210.1080/15440478.2023.22241242224124Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS MethodJing Ye0Ting-Yu Chen1Jiaxing UniversityChang Gung UniversitySelecting the best knitted fabric with various comfort properties is considered a complicated multi-criteria decision-making (MCDM) issue that involves ambiguity and vagueness. In such scenarios, Pythagorean fuzzy sets (PFSs) provide an effective tool for addressing uncertainty and ambiguity in MCDM problems that contain human subjective evaluations and judgments. First, this research identifies the factors affecting the comfort of knitted fabrics as the evaluation criteria. Second, the Bayesian best-worst method (BBWM) is preferred for less pairwise comparisons and obtains highly reliable results with a probabilistic perspective for determining the criteria weights. Furthermore, due to its logical computation approach and ease of operation, the technique for order preference by similarity to ideal solution (TOPSIS) is commonly utilized for addressing MCDM problems. Therefore, this research proposes an innovative MCDM framework that combines the BBWM technique with Pythagorean fuzzy TOPSIS (PFTOPSIS). The BBWM determines the criteria weights, and the weighted sine similarity-based PFTOPSIS is utilized to rank alternatives. The proposed BBWM-PFTOPSIS approach was employed to solve a real-world case. Moreover, this article conducts a sensitivity analysis and three comparative analyses to reveal the efficiency and reliability of the BBWM-PFTOPSIS approach. The ranking results establish the viability and effectiveness of BBWM-PFTOPSIS.http://dx.doi.org/10.1080/15440478.2023.2224124knitted fabricsmulti-criteria decision-making (mcdm)pythagorean fuzzy set (pfs)bayesian best-worst method (bbwm)technique for order preference by similarity to ideal solution (topsis)bbwm-pftopsis |
| spellingShingle | Jing Ye Ting-Yu Chen Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method Journal of Natural Fibers knitted fabrics multi-criteria decision-making (mcdm) pythagorean fuzzy set (pfs) bayesian best-worst method (bbwm) technique for order preference by similarity to ideal solution (topsis) bbwm-pftopsis |
| title | Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method |
| title_full | Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method |
| title_fullStr | Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method |
| title_full_unstemmed | Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method |
| title_short | Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method |
| title_sort | selection of knitted fabrics using a hybrid bbwm pftopsis method |
| topic | knitted fabrics multi-criteria decision-making (mcdm) pythagorean fuzzy set (pfs) bayesian best-worst method (bbwm) technique for order preference by similarity to ideal solution (topsis) bbwm-pftopsis |
| url | http://dx.doi.org/10.1080/15440478.2023.2224124 |
| work_keys_str_mv | AT jingye selectionofknittedfabricsusingahybridbbwmpftopsismethod AT tingyuchen selectionofknittedfabricsusingahybridbbwmpftopsismethod |