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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Main Authors: Zahra Dastani, Hamidreza Koosha, Hossein Karimi, Abolfazl Mohammadzadeh Moghaddam
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
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.
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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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AT hosseinkarimi userpreferencesinridesharingmathematicalmodelsforenhancedmatching
AT abolfazlmohammadzadehmoghaddam userpreferencesinridesharingmathematicalmodelsforenhancedmatching