IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i2p902-d481985.html
   My bibliography  Save this article

The Optimization Model of Ride-Sharing Route for Ride Hailing Considering Both System Optimization and User Fairness

Author

Listed:
  • Yi Cao

    (School of Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China)

  • Shan Wang

    (School of Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China)

  • Jinyang Li

    (School of Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China)

Abstract

To fully take the advantages of ride-sharing ride hailing, such as high loading rate, high operating efficiency, and less traffic resources, and to alleviate the difficulty of getting a taxi in urban hubs, the topic of ride-sharing route optimization for ride hailing is studied in this paper. For the multiple ride hailing ride-sharing demands and multiple ride hailing services in the urban road network in a specific period, the objective function is established with the shortest route of the system. The constraint conditions of the optimization model are constructed by considering factors of the rated passenger capacity, route rationality, passenger benefits, driver benefits and time window. Based on the idea of the Genetic Algorithm, the solution algorithm of the optimization model is developed. According to the supply and demand data of taxi during peak hours in the local road network in the city of Dalian, the optimization model and algorithm are used to optimize the ride-sharing route scheme. Research results indicate that the optimization model and algorithm can find the approximate optimal solution of the system in a short time. Compared with the traditional non-ride-sharing mode, the ride-sharing scheme can not only effectively reduce the taxi empty-loaded rate and the travel cost of passengers, improve the efficiency of drivers, but also save energy and reduce emissions, and promote the sustainable development of urban traffic.

Suggested Citation

  • Yi Cao & Shan Wang & Jinyang Li, 2021. "The Optimization Model of Ride-Sharing Route for Ride Hailing Considering Both System Optimization and User Fairness," Sustainability, MDPI, vol. 13(2), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:902-:d:481985
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/2/902/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/2/902/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lee, Alan & Savelsbergh, Martin, 2015. "Dynamic ridesharing: Is there a role for dedicated drivers?," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 483-497.
    2. Xin Li & Ming Wei & Jia Hu & Yun Yuan & Huifu Jiang, 2018. "An Agent-Based Model for Dispatching Real-Time Demand-Responsive Feeder Bus," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-11, March.
    3. Bian, Zheyong & Liu, Xiang & Bai, Yun, 2020. "Mechanism design for on-demand first-mile ridesharing," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 77-117.
    4. Stiglic, M. & Agatz, N.A.H. & Savelsbergh, M.W.P. & Gradisar, M., 2015. "The Benefits of Meeting Points in Ride-sharing Systems," ERIM Report Series Research in Management ERS-2015-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Xijun Zhang & Qirui Zhang & Zhanting Yuan & Chenhui Wang & Lijuan Zhang, 2020. "The Research on Planning of Taxi Sharing Route and Sharing Expenses," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, February.
    6. Li, Yuanyuan & Liu, Yang & Xie, Jun, 2020. "A path-based equilibrium model for ridesharing matching," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 373-405.
    7. Di, Xuan & Ma, Rui & Liu, Henry X. & Ban, Xuegang (Jeff), 2018. "A link-node reformulation of ridesharing user equilibrium with network design," Transportation Research Part B: Methodological, Elsevier, vol. 112(C), pages 230-255.
    8. Stiglic, Mitja & Agatz, Niels & Savelsbergh, Martin & Gradisar, Mirko, 2015. "The benefits of meeting points in ride-sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 36-53.
    9. Ma, Jie & Xu, Min & Meng, Qiang & Cheng, Lin, 2020. "Ridesharing user equilibrium problem under OD-based surge pricing strategy," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 1-24.
    10. Furuhata, Masabumi & Dessouky, Maged & Ordóñez, Fernando & Brunet, Marc-Etienne & Wang, Xiaoqing & Koenig, Sven, 2013. "Ridesharing: The state-of-the-art and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 28-46.
    11. Lei, Chao & Jiang, Zhoutong & Ouyang, Yanfeng, 2020. "Path-based dynamic pricing for vehicle allocation in ridesharing systems with fully compliant drivers," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 60-75.
    12. Changxi Ma & Ruichun He & Wei Zhang, 2018. "Path optimization of taxi carpooling," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-15, August.
    13. Tianlu Zhao & Yongjian Yang & En Wang, 2020. "Minimizing the average arriving distance in carpooling," International Journal of Distributed Sensor Networks, , vol. 16(1), pages 15501477198, January.
    14. Daganzo, Carlos F. & Ouyang, Yanfeng, 2019. "A general model of demand-responsive transportation services: From taxi to ridesharing to dial-a-ride," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 213-224.
    15. Naoum-Sawaya, Joe & Cogill, Randy & Ghaddar, Bissan & Sajja, Shravan & Shorten, Robert & Taheri, Nicole & Tommasi, Pierpaolo & Verago, Rudi & Wirth, Fabian, 2015. "Stochastic optimization approach for the car placement problem in ridesharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 173-184.
    16. Long, Jiancheng & Tan, Weimin & Szeto, W.Y. & Li, Yao, 2018. "Ride-sharing with travel time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 143-171.
    17. Masoud, Neda & Jayakrishnan, R., 2017. "A real-time algorithm to solve the peer-to-peer ride-matching problem in a flexible ridesharing system," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 218-236.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Seyed Omid Hasanpour Jesri & Mohsen Akbarpour Shirazi, 2022. "Bi Objective Peer-to-Peer Ridesharing Model for Balancing Passengers Time and Costs," Sustainability, MDPI, vol. 14(12), pages 1-24, June.
    2. Rashmi Bhardwaj & Shanky Garg, 2024. "Multi-objective and blockchain based optimization algorithm for fleet sharing management," OPSEARCH, Springer;Operational Research Society of India, vol. 61(3), pages 1131-1153, September.
    3. Guo, Yuhan & Zhang, Yu & Boulaksil, Youssef & Qian, Yaguan & Allaoui, Hamid, 2023. "Modelling and analysis of online ride-sharing platforms – A sustainability perspective," European Journal of Operational Research, Elsevier, vol. 304(2), pages 577-595.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ke, Jintao & Yang, Hai & Li, Xinwei & Wang, Hai & Ye, Jieping, 2020. "Pricing and equilibrium in on-demand ride-pooling markets," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 411-431.
    2. Long, Jiancheng & Tan, Weimin & Szeto, W.Y. & Li, Yao, 2018. "Ride-sharing with travel time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 143-171.
    3. Xingyuan Li & Jing Bai, 2021. "A Ridesharing Choice Behavioral Equilibrium Model with Users of Heterogeneous Values of Time," IJERPH, MDPI, vol. 18(3), pages 1-22, January.
    4. Wang, Jing-Peng & Ban, Xuegang (Jeff) & Huang, Hai-Jun, 2019. "Dynamic ridesharing with variable-ratio charging-compensation scheme for morning commute," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 390-415.
    5. Peng, Zixuan & Shan, Wenxuan & Zhu, Xiaoning & Yu, Bin, 2022. "Many-to-one stable matching for taxi-sharing service with selfish players," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 255-279.
    6. Alnaggar, Aliaa & Gzara, Fatma & Bookbinder, James H., 2021. "Crowdsourced delivery: A review of platforms and academic literature," Omega, Elsevier, vol. 98(C).
    7. Sun, S. & Szeto, W.Y., 2021. "Multi-class stochastic user equilibrium assignment model with ridesharing: Formulation and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 203-227.
    8. Ke, Jintao & Yang, Hai & Zheng, Zhengfei, 2020. "On ride-pooling and traffic congestion," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 213-231.
    9. Ruijie Li & Yu (Marco) Nie & Xiaobo Liu, 2020. "Pricing Carpool Rides Based on Schedule Displacement," Transportation Science, INFORMS, vol. 54(4), pages 1134-1152, July.
    10. Huang, Zhihui & Long, Jiancheng & Szeto, W.Y. & Liu, Haoxiang, 2021. "Modeling and managing the morning commute problem with park-and-ride-sharing," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 190-226.
    11. Omer Faruk Aydin & Ilgin Gokasar & Onur Kalan, 2020. "Matching algorithm for improving ride-sharing by incorporating route splits and social factors," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-23, March.
    12. Li, Yuanyuan & Liu, Yang & Xie, Jun, 2020. "A path-based equilibrium model for ridesharing matching," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 373-405.
    13. Liu, Yining & Ouyang, Yanfeng, 2023. "Planning ride-pooling services with detour restrictions for spatially heterogeneous demand: A multi-zone queuing network approach," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    14. Wenyi Chen & Martijn Mes & Marco Schutten & Job Quint, 2019. "A Ride-Sharing Problem with Meeting Points and Return Restrictions," Transportation Science, INFORMS, vol. 53(2), pages 401-426, March.
    15. Meng Li & Guowei Hua & Haijun Huang, 2018. "A Multi-Modal Route Choice Model with Ridesharing and Public Transit," Sustainability, MDPI, vol. 10(11), pages 1-14, November.
    16. Horner, Hannah & Pazour, Jennifer & Mitchell, John E., 2021. "Optimizing driver menus under stochastic selection behavior for ridesharing and crowdsourced delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    17. Li, Tongfei & Xu, Min & Sun, Huijun & Xiong, Jie & Dou, Xueping, 2023. "Stochastic ridesharing equilibrium problem with compensation optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    18. Zhong, Lin & Zhang, Kenan & (Marco) Nie, Yu & Xu, Jiuping, 2020. "Dynamic carpool in morning commute: Role of high-occupancy-vehicle (HOV) and high-occupancy-toll (HOT) lanes," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 98-119.
    19. Stiglic, M. & Agatz, N.A.H. & Savelsbergh, M.W.P. & Gradisar, M., 2016. "Enhancing Urban Mobility: Integrating Ride-sharing and Public Transit," ERIM Report Series Research in Management ERS-2016-006-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    20. Tao Yang & Weixin Wang, 2022. "Logistics Network Distribution Optimization Based on Vehicle Sharing," Sustainability, MDPI, vol. 14(4), pages 1-12, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:902-:d:481985. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.