IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i4p2124-d748259.html
   My bibliography  Save this article

The One E-Ticket Customized Bus Service Mode for Passengers with Multiple Trips and the Routing Problem

Author

Listed:
  • Yunlin Guan

    (MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Yun Wang

    (MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Xuedong Yan

    (MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Haonan Guo

    (MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Yi Zhao

    (Standards and Metrology Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China)

Abstract

To alleviate the problems of traffic congestion, excessive energy consumption, and the environmental pollution caused by private cars, it is essential to use public transportation (PT). However, passengers making multiple trips in a short time period must repeatedly make travel mode choices, purchase tickets, and wait for buses for each trip, which may negatively affect their preference for PT. In order to improve the attractiveness of PT, especially for passengers requiring multiple trips in a short time period, this paper proposes the one e-ticket customized bus service mode for passengers with multiple trips (OECBSM-PMT) by customized buses (CBs). Besides, a CB-routing optimization model for the OECBSM-PMT is also developed in this paper, formulated as a mixed-integer linear programming based on a vehicle routing problem with pickup and delivery and time windows (VRPPDTW). The model aims to maximize the profit and minimize the costs of operation with considering passengers with multi-trip requests, homogeneous CB fleets with pickup/delivery-time-window constraints, and mixed loads. A service effectiveness identification procedure based on genetic algorithm (GA) is proposed to cope with the calculation considering the characteristics of passengers with multiple trips. Finally, the proposed model and algorithm are verified and analyzed using the case of the 2022 Beijing Winter Olympic Games. It can be found from the results that the method can provide an optimized CB route plan and timetable, and the algorithm GA-I obtains better solutions than other solving strategies in most instances. The proposed OECBSM-PMT and corresponding optimized method can better adapt to diverse travel demands, significantly improve the convenience for passengers, especially those making multiple trips in a short time period and will eventually promote a higher level of public transport service.

Suggested Citation

  • Yunlin Guan & Yun Wang & Xuedong Yan & Haonan Guo & Yi Zhao, 2022. "The One E-Ticket Customized Bus Service Mode for Passengers with Multiple Trips and the Routing Problem," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2124-:d:748259
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/4/2124/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/4/2124/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    2. Yang Cao & Jian Wang, 2017. "An Optimization Method of Passenger Assignment for Customized Bus," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-9, June.
    3. Cordeau, Jean-François & Laporte, Gilbert, 2003. "A tabu search heuristic for the static multi-vehicle dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 37(6), pages 579-594, July.
    4. Yanik, Seda & Bozkaya, Burcin & deKervenoael, Ronan, 2014. "A new VRPPD model and a hybrid heuristic solution approach for e-tailing," European Journal of Operational Research, Elsevier, vol. 236(3), pages 879-890.
    5. Roberto Baldacci & Enrico Bartolini & Aristide Mingozzi, 2011. "An Exact Algorithm for the Pickup and Delivery Problem with Time Windows," Operations Research, INFORMS, vol. 59(2), pages 414-426, April.
    6. Lauri Häme & Harri Hakula, 2015. "A Maximum Cluster Algorithm for Checking the Feasibility of Dial-A-Ride Instances," Transportation Science, INFORMS, vol. 49(2), pages 295-310, May.
    7. Liu, Tao & Ceder, Avishai (Avi), 2015. "Analysis of a new public-transport-service concept: Customized bus in China," Transport Policy, Elsevier, vol. 39(C), pages 63-76.
    8. Zhiling Han & Yanyan Chen & Hui Li & Kuanshuang Zhang & Jiyang Sun, 2019. "Customized Bus Network Design Based on Individual Reservation Demands," Sustainability, MDPI, vol. 11(19), pages 1-25, October.
    9. Jean-François Cordeau, 2006. "A Branch-and-Cut Algorithm for the Dial-a-Ride Problem," Operations Research, INFORMS, vol. 54(3), pages 573-586, June.
    10. Sai Shao & Wei Guan & Bin Ran & Zhengbing He & Jun Bi, 2017. "Electric Vehicle Routing Problem with Charging Time and Variable Travel Time," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-13, January.
    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. Xinhua Gao & Song Liu & Yan Wang & Dennis Z. Yu & Yong Peng & Xianting Ma, 2024. "Consideration of Carbon Emissions in Multi-Trip Delivery Optimization of Unmanned Vehicles," Sustainability, MDPI, vol. 16(6), pages 1-26, March.
    2. Guan, Yunlin & Xiang, Wang & Wang, Yun & Yan, Xuedong & Zhao, Yi, 2023. "Bi-level optimization for customized bus routing serving passengers with multiple-trips based on state–space–time network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).

    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. Schaumann, Sarah K. & Bergmann, Felix M. & Wagner, Stephan M. & Winkenbach, Matthias, 2023. "Route efficiency implications of time windows and vehicle capacities in first- and last-mile logistics," European Journal of Operational Research, Elsevier, vol. 311(1), pages 88-111.
    2. Lee, Enoch & Cen, Xuekai & Lo, Hong K., 2021. "Zonal-based flexible bus service under elastic stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    3. Mahmoudi, Monirehalsadat & Chen, Junhua & Shi, Tie & Zhang, Yongxiang & Zhou, Xuesong, 2019. "A cumulative service state representation for the pickup and delivery problem with transfers," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 351-380.
    4. Gong, Manlin & Hu, Yucong & Chen, Zhiwei & Li, Xiaopeng, 2021. "Transfer-based customized modular bus system design with passenger-route assignment optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    5. Timo Gschwind & Michael Drexl, 2016. "Adaptive Large Neighborhood Search with a Constant-Time Feasibility Test for the Dial-a-Ride Problem," Working Papers 1624, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    6. Luciano Costa & Claudio Contardo & Guy Desaulniers, 2019. "Exact Branch-Price-and-Cut Algorithms for Vehicle Routing," Transportation Science, INFORMS, vol. 53(4), pages 946-985, July.
    7. Liu, Jiaguo & Zhao, Huida & Li, Jian & Yue, Xiaohang, 2021. "Operational strategy of customized bus considering customers’ variety seeking behavior and service level," International Journal of Production Economics, Elsevier, vol. 231(C).
    8. Liu, Mengyang & Luo, Zhixing & Lim, Andrew, 2015. "A branch-and-cut algorithm for a realistic dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 267-288.
    9. Schulz, Arne & Pfeiffer, Christian, 2024. "Using fixed paths to improve branch-and-cut algorithms for precedence-constrained routing problems," European Journal of Operational Research, Elsevier, vol. 312(2), pages 456-472.
    10. Sophie N. Parragh & Jorge Pinho de Sousa & Bernardo Almada-Lobo, 2015. "The Dial-a-Ride Problem with Split Requests and Profits," Transportation Science, INFORMS, vol. 49(2), pages 311-334, May.
    11. Claudio Gambella & Joe Naoum-Sawaya & Bissan Ghaddar, 2018. "The Vehicle Routing Problem with Floating Targets: Formulation and Solution Approaches," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 554-569, August.
    12. Bongiovanni, Claudia & Kaspi, Mor & Geroliminis, Nikolas, 2019. "The electric autonomous dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 436-456.
    13. Zhang, Zhenzhen & Liu, Mengyang & Lim, Andrew, 2015. "A memetic algorithm for the patient transportation problem," Omega, Elsevier, vol. 54(C), pages 60-71.
    14. Wang, Hongfei & Guan, Hongzhi & Qin, Huanmei & Zhao, Pengfei, 2024. "Assessing the sustainability of time-dependent electric demand responsive transit service through deep reinforcement learning," Energy, Elsevier, vol. 296(C).
    15. Ertan Yakıcı & Robert F. Dell & Travis Hartman & Connor McLemore, 2018. "Daily aircraft routing for amphibious ready groups," Annals of Operations Research, Springer, vol. 264(1), pages 477-498, May.
    16. Ho, Sin C. & Szeto, W.Y. & Kuo, Yong-Hong & Leung, Janny M.Y. & Petering, Matthew & Tou, Terence W.H., 2018. "A survey of dial-a-ride problems: Literature review and recent developments," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 395-421.
    17. Christian Pfeiffer & Arne Schulz, 2022. "An ALNS algorithm for the static dial-a-ride problem with ride and waiting time minimization," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 87-119, March.
    18. Zhang, Li & Liu, Zhongshan & Yu, Bin & Long, Jiancheng, 2024. "A ridesharing routing problem for airport riders with electric vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    19. Andrew Lim & Zhenzhen Zhang & Hu Qin, 2017. "Pickup and Delivery Service with Manpower Planning in Hong Kong Public Hospitals," Transportation Science, INFORMS, vol. 51(2), pages 688-705, May.
    20. Detti, Paolo & Papalini, Francesco & Lara, Garazi Zabalo Manrique de, 2017. "A multi-depot dial-a-ride problem with heterogeneous vehicles and compatibility constraints in healthcare," Omega, Elsevier, vol. 70(C), pages 1-14.

    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:14:y:2022:i:4:p:2124-:d:748259. 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.