IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i3p897-d312960.html
   My bibliography  Save this article

Demand Responsive Service-based Optimization on Flexible Routes and Departure Time of Community Shuttles

Author

Listed:
  • Jie Xiong

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

  • Biao Chen

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

  • Xiangnan Li

    (China Airport Planning & Design Institute Co., Ltd, Beijing 100101, China)

  • Zhengbing He

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
    Guangdong Provincial Key Laboratory of Intelligent Transportation System, School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510275, China)

  • Yanyan Chen

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

Abstract

This paper investigates the optimal routing design problem of a community shuttle system feeding to metro stations based on demand-responsive service. The solution aims to jointly optimize a set of customized routes and the departure time of each route to provide a flexible shuttle service. Considering a set of on-demand trip requests between bus stops and metro stations, a mixed-integer optimization model is formulated to minimize the total system cost, including the operation cost and passenger’s in-vehicle cost, subject to the constraints on the route length, time window, detours, and vehicle capacity. To solve the problem, two metaheuristic algorithms, i.e. a tabu search (TS) and a variable neighborhood search (VNS), with different internal operators are specifically designed. A case study based on a realistic network is conducted to test the model and the solution, and comparisons of the performance of different algorithms are investigated.

Suggested Citation

  • Jie Xiong & Biao Chen & Xiangnan Li & Zhengbing He & Yanyan Chen, 2020. "Demand Responsive Service-based Optimization on Flexible Routes and Departure Time of Community Shuttles," Sustainability, MDPI, vol. 12(3), pages 1-20, January.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:897-:d:312960
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/3/897/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/3/897/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gonzales, Eric J., 2016. "Demand responsive transit systems with time-dependent demand: User equilibrium, system optimum, and management strategyAuthor-Name: Amirgholy, Mahyar," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 234-252.
    2. T. Ibaraki & S. Imahori & M. Kubo & T. Masuda & T. Uno & M. Yagiura, 2005. "Effective Local Search Algorithms for Routing and Scheduling Problems with General Time-Window Constraints," Transportation Science, INFORMS, vol. 39(2), pages 206-232, May.
    3. 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.
    4. Naccache, Salma & Côté, Jean-François & Coelho, Leandro C., 2018. "The multi-pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 269(1), pages 353-362.
    5. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    6. Irnich, Stefan, 2000. "A multi-depot pickup and delivery problem with a single hub and heterogeneous vehicles," European Journal of Operational Research, Elsevier, vol. 122(2), pages 310-328, April.
    7. Shixiong Jiang & Wei Guan & Zhengbing He & Liu Yang, 2018. "Measuring Taxi Accessibility Using Grid-Based Method with Trajectory Data," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    8. 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.
    9. Haddad, Matheus Nohra & Martinelli, Rafael & Vidal, Thibaut & Martins, Simone & Ochi, Luiz Satoru & Souza, Marcone Jamilson Freitas & Hartl, Richard, 2018. "Large neighborhood-based metaheuristic and branch-and-price for the pickup and delivery problem with split loads," European Journal of Operational Research, Elsevier, vol. 270(3), pages 1014-1027.
    10. Stefan Ropke & Jean-François Cordeau, 2009. "Branch and Cut and Price for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 43(3), pages 267-286, August.
    11. Reinhardt, Line Blander & Clausen, Tommy & Pisinger, David, 2013. "Synchronized dial-a-ride transportation of disabled passengers at airports," European Journal of Operational Research, Elsevier, vol. 225(1), pages 106-117.
    12. Braekers, Kris & Caris, An & Janssens, Gerrit K., 2014. "Exact and meta-heuristic approach for a general heterogeneous dial-a-ride problem with multiple depots," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 166-186.
    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. András Lakatos & János Tóth & Péter Mándoki, 2020. "Demand Responsive Transport Service of ‘Dead-End Villages’ in Interurban Traffic," Sustainability, MDPI, vol. 12(9), pages 1-17, May.
    2. Xudong Li & Zhongzhen Yang & Feng Lian, 2023. "Optimizing On-Demand Bus Services for Remote Areas," Sustainability, MDPI, vol. 15(9), pages 1-20, April.

    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. 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.
    2. Masmoudi, Mohamed Amine & Hosny, Manar & Demir, Emrah & Genikomsakis, Konstantinos N. & Cheikhrouhou, Naoufel, 2018. "The dial-a-ride problem with electric vehicles and battery swapping stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 392-420.
    3. Guo, Jiaqi & Long, Jiancheng & Xu, Xiaoming & Yu, Miao & Yuan, Kai, 2022. "The vehicle routing problem of intercity ride-sharing between two cities," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 113-139.
    4. Wang, Yuan & Lei, Linfei & Zhang, Dongxiang & Lee, Loo Hay, 2020. "Towards delivery-as-a-service: Effective neighborhood search strategies for integrated delivery optimization of E-commerce and static O2O parcels," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 38-63.
    5. Johnsen, Lennart C. & Meisel, Frank, 2022. "Interrelated trips in the rural dial-a-ride problem with autonomous vehicles," European Journal of Operational Research, Elsevier, vol. 303(1), pages 201-219.
    6. Yves Molenbruch & Kris Braekers & An Caris, 2017. "Typology and literature review for dial-a-ride problems," Annals of Operations Research, Springer, vol. 259(1), pages 295-325, December.
    7. 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.
    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. Li, Chongshou & Gong, Lijun & Luo, Zhixing & Lim, Andrew, 2019. "A branch-and-price-and-cut algorithm for a pickup and delivery problem in retailing," Omega, Elsevier, vol. 89(C), pages 71-91.
    11. Zhang, Zhenzhen & Liu, Mengyang & Lim, Andrew, 2015. "A memetic algorithm for the patient transportation problem," Omega, Elsevier, vol. 54(C), pages 60-71.
    12. 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.
    13. Hou, Liwen & Li, Dong & Zhang, Dali, 2018. "Ride-matching and routing optimisation: Models and a large neighbourhood search heuristic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 143-162.
    14. Braekers, Kris & Kovacs, Attila A., 2016. "A multi-period dial-a-ride problem with driver consistency," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 355-377.
    15. Negin Alisoltani & Mostafa Ameli & Mahdi Zargayouna & Ludovic Leclercq, 2022. "Space-time clustering-based method to optimize shareability in real-time ride-sharing," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-25, January.
    16. Gaul, Daniela & Klamroth, Kathrin & Stiglmayr, Michael, 2022. "Event-based MILP models for ridepooling applications," European Journal of Operational Research, Elsevier, vol. 301(3), pages 1048-1063.
    17. Margaretha Gansterer & Richard F. Hartl & Philipp E. H. Salzmann, 2018. "Exact solutions for the collaborative pickup and delivery problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(2), pages 357-371, June.
    18. Timo Gschwind & Michael Drexl, 2019. "Adaptive Large Neighborhood Search with a Constant-Time Feasibility Test for the Dial-a-Ride Problem," Transportation Science, INFORMS, vol. 53(2), pages 480-491, March.
    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:12:y:2020:i:3:p:897-:d:312960. 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.