Optimizing Automotive Logistics Using MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic Application
The domain of decision-making theory has made significant progress, especially within the industrial and management fields. Diverse decision-making challenges such as multicriteria decision-making (MCDM), multiattribute decision-making (MADM), and multiattribute group decision-making (MAGDM) have be...
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Wiley
2024-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/adfs/7672845 |
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| author | Kalaivani Kaspar Palanivel Kaliyaperumal |
| author_facet | Kalaivani Kaspar Palanivel Kaliyaperumal |
| author_sort | Kalaivani Kaspar |
| collection | DOAJ |
| description | The domain of decision-making theory has made significant progress, especially within the industrial and management fields. Diverse decision-making challenges such as multicriteria decision-making (MCDM), multiattribute decision-making (MADM), and multiattribute group decision-making (MAGDM) have been thoroughly examined, equipping decision-makers with effective strategies for tackling these issues. In the context of the automotive industry, a specific hurdle emerges when identifying the most suitable site for establishing a warehouse to store goods destined for multiple destinations. This article addresses a scenario amid uncertainty, leveraging substantial data. Neutrosophic sets (NSs) emerge as a comprehensive tool for effectively managing the imprecision inherent in such data. Among these sets, single-valued neutrosophic sets (SVNSs) stand out due to their adeptness in handling inconsistent or incomplete data. The octagonal single-valued neutrosophic numbers (OSVNNs) has a new tool for representing the uncertainty information in a simplified manner. Octagonal structure allows for representing different distinctions of truth, neutrality, and falsity of any complex situation and it is an efficient tool to compare different options based on their level of ambiguity. They have a wide range of applications in various fields, becoming increasingly important in addressing many difficult and uncertain issues. The article aims to propose a new ranking function for OSVNNs to convert the OSVNN data into precise values, drawing from the existing mean interval method (MIM). The conventional decision-making approaches such as weighted sum model (WSM), weighted product model (WPM), technique for order of preference by similarity to ideal solution (TOPSIS), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) are employed to obtain the optimal warehouse location using OSVN application. Furthermore, it demonstrates the application along with the proposed ranking function using the software MATLAB to determine the most favorable alternatives. Finally, sensitivity analyses are performed to assess how different scenarios could impact the optimal location selection for automotive logistics. |
| format | Article |
| id | doaj-art-3f41e897e177473fb7fe8368e86f5068 |
| institution | Kabale University |
| issn | 1687-711X |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-3f41e897e177473fb7fe8368e86f50682025-01-08T00:00:02ZengWileyAdvances in Fuzzy Systems1687-711X2024-01-01202410.1155/adfs/7672845Optimizing Automotive Logistics Using MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic ApplicationKalaivani Kaspar0Palanivel Kaliyaperumal1Department of MathematicsDepartment of MathematicsThe domain of decision-making theory has made significant progress, especially within the industrial and management fields. Diverse decision-making challenges such as multicriteria decision-making (MCDM), multiattribute decision-making (MADM), and multiattribute group decision-making (MAGDM) have been thoroughly examined, equipping decision-makers with effective strategies for tackling these issues. In the context of the automotive industry, a specific hurdle emerges when identifying the most suitable site for establishing a warehouse to store goods destined for multiple destinations. This article addresses a scenario amid uncertainty, leveraging substantial data. Neutrosophic sets (NSs) emerge as a comprehensive tool for effectively managing the imprecision inherent in such data. Among these sets, single-valued neutrosophic sets (SVNSs) stand out due to their adeptness in handling inconsistent or incomplete data. The octagonal single-valued neutrosophic numbers (OSVNNs) has a new tool for representing the uncertainty information in a simplified manner. Octagonal structure allows for representing different distinctions of truth, neutrality, and falsity of any complex situation and it is an efficient tool to compare different options based on their level of ambiguity. They have a wide range of applications in various fields, becoming increasingly important in addressing many difficult and uncertain issues. The article aims to propose a new ranking function for OSVNNs to convert the OSVNN data into precise values, drawing from the existing mean interval method (MIM). The conventional decision-making approaches such as weighted sum model (WSM), weighted product model (WPM), technique for order of preference by similarity to ideal solution (TOPSIS), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) are employed to obtain the optimal warehouse location using OSVN application. Furthermore, it demonstrates the application along with the proposed ranking function using the software MATLAB to determine the most favorable alternatives. Finally, sensitivity analyses are performed to assess how different scenarios could impact the optimal location selection for automotive logistics.http://dx.doi.org/10.1155/adfs/7672845 |
| spellingShingle | Kalaivani Kaspar Palanivel Kaliyaperumal Optimizing Automotive Logistics Using MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic Application Advances in Fuzzy Systems |
| title | Optimizing Automotive Logistics Using MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic Application |
| title_full | Optimizing Automotive Logistics Using MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic Application |
| title_fullStr | Optimizing Automotive Logistics Using MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic Application |
| title_full_unstemmed | Optimizing Automotive Logistics Using MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic Application |
| title_short | Optimizing Automotive Logistics Using MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic Application |
| title_sort | optimizing automotive logistics using mcgdm a data driven approach to the selection of warehouse location with octagonal neutrosophic application |
| url | http://dx.doi.org/10.1155/adfs/7672845 |
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