IDEAS home Printed from https://ideas.repec.org/a/ibn/cisjnl/v14y2021i1p8.html
   My bibliography  Save this article

An O(nlogn/logw) Time Algorithm for Ridesharing

Author

Listed:
  • Yijie Han
  • Chen Sun

Abstract

In the ridesharing problem different people share private vehicles because they have similar itineraries. The objective of solving the ridesharing problem is to minimize the number of drivers needed to carry all load to the destination. The general case of ridesharing problem is NP-complete. For the special case where the network is a chain and the destination is the leftmost vertex of the chain, we present an O(nlogn/logw) time algorithm for the ridesharing problem, where w is the word length used in the algorithm and is at least logn. Previous achieved algorithm for this case requires O(nlogn) time.

Suggested Citation

  • Yijie Han & Chen Sun, 2021. "An O(nlogn/logw) Time Algorithm for Ridesharing," Computer and Information Science, Canadian Center of Science and Education, vol. 14(1), pages 1-8, February.
  • Handle: RePEc:ibn:cisjnl:v:14:y:2021:i:1:p:8
    as

    Download full text from publisher

    File URL: http://www.ccsenet.org/journal/index.php/cis/article/download/0/0/44549/47014
    Download Restriction: no

    File URL: http://www.ccsenet.org/journal/index.php/cis/article/view/0/44549
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Roberto Baldacci & Vittorio Maniezzo & Aristide Mingozzi, 2004. "An Exact Method for the Car Pooling Problem Based on Lagrangean Column Generation," Operations Research, INFORMS, vol. 52(3), pages 422-439, June.
    Full references (including those not matched with items on IDEAS)

    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. Moon, Ilkyeong & Feng, Xuehao, 2017. "Supply chain coordination with a single supplier and multiple retailers considering customer arrival times and route selection," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 78-97.
    2. Shangyao Yan & Chun-Ying Chen & Chuan-Che Wu, 2012. "Solution methods for the taxi pooling problem," Transportation, Springer, vol. 39(3), pages 723-748, May.
    3. Li, Zhaojin & Liu, Ya & Yang, Zhen, 2021. "An effective kernel search and dynamic programming hybrid heuristic for a multimodal transportation planning problem with order consolidation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    4. Hosni, Hadi & Naoum-Sawaya, Joe & Artail, Hassan, 2014. "The shared-taxi problem: Formulation and solution methods," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 303-318.
    5. Agatz, Niels & Erera, Alan & Savelsbergh, Martin & Wang, Xing, 2012. "Optimization for dynamic ride-sharing: A review," European Journal of Operational Research, Elsevier, vol. 223(2), pages 295-303.
    6. Xing Wang & Niels Agatz & Alan Erera, 2018. "Stable Matching for Dynamic Ride-Sharing Systems," Transportation Science, INFORMS, vol. 52(4), pages 850-867, August.
    7. 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.
    8. Masoud, Neda & Jayakrishnan, R., 2017. "A decomposition algorithm to solve the multi-hop Peer-to-Peer ride-matching problem," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 1-29.
    9. 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.
    10. 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.
    11. Yi, Xu & Lian, Feng & Yang, Zhongzhen, 2022. "Research on commuters’ carpooling behavior in the mobile internet context," Transport Policy, Elsevier, vol. 126(C), pages 14-25.
    12. Amirmahdi Tafreshian & Neda Masoud & Yafeng Yin, 2020. "Frontiers in Service Science: Ride Matching for Peer-to-Peer Ride Sharing: A Review and Future Directions," Service Science, INFORMS, vol. 12(2-3), pages 44-60, June.
    13. Guo, Yuhan & Zhang, Yu & Boulaksil, Youssef, 2021. "Real-time ride-sharing framework with dynamic timeframe and anticipation-based migration," European Journal of Operational Research, Elsevier, vol. 288(3), pages 810-828.
    14. Bian, Zheyong & Liu, Xiang, 2019. "Mechanism design for first-mile ridesharing based on personalized requirements part I: Theoretical analysis in generalized scenarios," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 147-171.
    15. Enzi, Miriam & Parragh, Sophie N. & Pisinger, David & Prandtstetter, Matthias, 2021. "Modeling and solving the multimodal car- and ride-sharing problem," European Journal of Operational Research, Elsevier, vol. 293(1), pages 290-303.
    16. Mohammad Asghari & Seyed Mohammad Javad Mirzapour Al-E-Hashem & Yacine Rekik, 2022. "Environmental and social implications of incorporating carpooling service on a customized bus system," Post-Print hal-03598768, HAL.
    17. Mourad, Abood & Puchinger, Jakob & Chu, Chengbin, 2019. "A survey of models and algorithms for optimizing shared mobility," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 323-346.
    18. Schulz, Arne & Pfeiffer, Christian, 2024. "A Branch-and-Cut algorithm for the dial-a-ride problem with incompatible customer types," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    19. Guo, Xiaotong & Caros, Nicholas S. & Zhao, Jinhua, 2021. "Robust matching-integrated vehicle rebalancing in ride-hailing system with uncertain demand," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 161-189.
    20. Agatz, N.A.H. & Erera, A. & Savelsbergh, M.W.P. & Wang, X., 2010. "Sustainable Passenger Transportation: Dynamic Ride-Sharing," ERIM Report Series Research in Management ERS-2010-010-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.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    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:ibn:cisjnl:v:14:y:2021:i:1:p:8. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.