User preferences in ride-sharing mathematical models for enhanced matching
Abstract Ride-sharing services have attracted significant interest due to overcrowding, limited energy resources, and environmental concerns. This study proposes a mathematical programming model that integrates user preferences into the ride-sharing problem with transfer. Passenger transfer in ride-...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-11-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-78469-1 |
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| author | Zahra Dastani Hamidreza Koosha Hossein Karimi Abolfazl Mohammadzadeh Moghaddam |
| author_facet | Zahra Dastani Hamidreza Koosha Hossein Karimi Abolfazl Mohammadzadeh Moghaddam |
| author_sort | Zahra Dastani |
| collection | DOAJ |
| description | Abstract Ride-sharing services have attracted significant interest due to overcrowding, limited energy resources, and environmental concerns. This study proposes a mathematical programming model that integrates user preferences into the ride-sharing problem with transfer. Passenger transfer in ride-sharing problems addresses the limitations of the matching process, especially in less-populated areas. It allows passengers to be dropped off at meeting points and continue with another driver. Moreover, considering user preferences in ride-sharing systems is crucial for enhancing efficiency and user satisfaction. Accordingly, we propose a Preference-Driven Matching Algorithm for the matching process. Our proposed algorithm captures user preferences and provides potential matches. In addition, we introduce an Iterative Enhance-and-Optimize Algorithm capable of producing high-quality solutions within short computational times. We evaluate the efficiency of these approaches across various instances, focusing on real-scale scenarios. Based on the results, the model with preferences demonstrates effective performance compared to other methods. Our findings underscore the importance of user preferences in optimizing ride-sharing problems and highlight the trade-off between efficiency and user satisfaction. By incorporating user preferences, our approach results in higher user satisfaction, a more responsive and efficient system with reduced response times, and increased demand and revenue by servicing more users. |
| format | Article |
| id | doaj-art-a6d973df2c64403fb6a2014f0a8a0769 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-a6d973df2c64403fb6a2014f0a8a07692025-08-20T02:50:00ZengNature PortfolioScientific Reports2045-23222024-11-0114112010.1038/s41598-024-78469-1User preferences in ride-sharing mathematical models for enhanced matchingZahra Dastani0Hamidreza Koosha1Hossein Karimi2Abolfazl Mohammadzadeh Moghaddam3Department of Industrial Engineering, Ferdowsi University of MashhadDepartment of Industrial Engineering, Ferdowsi University of MashhadDepartment of Industrial Engineering, University of BojnordDepartment of Civil Engineering, Ferdowsi University of MashhadAbstract Ride-sharing services have attracted significant interest due to overcrowding, limited energy resources, and environmental concerns. This study proposes a mathematical programming model that integrates user preferences into the ride-sharing problem with transfer. Passenger transfer in ride-sharing problems addresses the limitations of the matching process, especially in less-populated areas. It allows passengers to be dropped off at meeting points and continue with another driver. Moreover, considering user preferences in ride-sharing systems is crucial for enhancing efficiency and user satisfaction. Accordingly, we propose a Preference-Driven Matching Algorithm for the matching process. Our proposed algorithm captures user preferences and provides potential matches. In addition, we introduce an Iterative Enhance-and-Optimize Algorithm capable of producing high-quality solutions within short computational times. We evaluate the efficiency of these approaches across various instances, focusing on real-scale scenarios. Based on the results, the model with preferences demonstrates effective performance compared to other methods. Our findings underscore the importance of user preferences in optimizing ride-sharing problems and highlight the trade-off between efficiency and user satisfaction. By incorporating user preferences, our approach results in higher user satisfaction, a more responsive and efficient system with reduced response times, and increased demand and revenue by servicing more users.https://doi.org/10.1038/s41598-024-78469-1Ride-sharingUser preferenceTransferSatisfactionMatching |
| spellingShingle | Zahra Dastani Hamidreza Koosha Hossein Karimi Abolfazl Mohammadzadeh Moghaddam User preferences in ride-sharing mathematical models for enhanced matching Scientific Reports Ride-sharing User preference Transfer Satisfaction Matching |
| title | User preferences in ride-sharing mathematical models for enhanced matching |
| title_full | User preferences in ride-sharing mathematical models for enhanced matching |
| title_fullStr | User preferences in ride-sharing mathematical models for enhanced matching |
| title_full_unstemmed | User preferences in ride-sharing mathematical models for enhanced matching |
| title_short | User preferences in ride-sharing mathematical models for enhanced matching |
| title_sort | user preferences in ride sharing mathematical models for enhanced matching |
| topic | Ride-sharing User preference Transfer Satisfaction Matching |
| url | https://doi.org/10.1038/s41598-024-78469-1 |
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