IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i11p6325-d567844.html
   My bibliography  Save this article

A Heuristic Method for Bus Rapid Transit Planning Based on the Maximum Trip Service

Author

Listed:
  • Zhong Wang

    (School of Transportation and Logistics, Dalian University of Technology, 2 Linggong Road, Dalian 116024, China)

  • Fengmin Lan

    (Jiangsu Kejia Engineering Design Co., Ltd., 21 Jiefangbei Road, Wuxi 214000, China)

  • Zijing Lin

    (School of Transportation and Logistics, Dalian University of Technology, 2 Linggong Road, Dalian 116024, China)

  • Lian Lian

    (School of Transportation and Logistics, Dalian University of Technology, 2 Linggong Road, Dalian 116024, China)

Abstract

Bus rapid transit (BRT) is characterized by higher speed, higher comfort level, and larger capacity than conventional bus service. Although many cities worldwide have adopted BRT in recent years, there is an absence of scientific and quantitative approach for BRT network planning. The problem of BRT planning in an existing transportation network is very complex with constraints of road geometrics, regulations, right of way, travel demand, vehicle operations, and so on. This paper focuses on developing an optimization model for BRT network planning, where an integer programing model is established to identify station locations and route layout with the objective of maximizing the number of trips served by the network, subjected to constraints including distance between stations, cost of construction, road geometrics, etc. The detour factor of the BRT route, which is an important indicator but widely ignored in previous studies, is also taken as a constraint. A heuristic method is applied to generate optimal solutions to the integer programming model, followed by a case study using the transportation network and travel demand data in Luoyang, China. The numerical results show that the method is valid and can therefore be applied to improve BRT network planning and the sustainable transportation system development.

Suggested Citation

  • Zhong Wang & Fengmin Lan & Zijing Lin & Lian Lian, 2021. "A Heuristic Method for Bus Rapid Transit Planning Based on the Maximum Trip Service," Sustainability, MDPI, vol. 13(11), pages 1-12, June.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:11:p:6325-:d:567844
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/11/6325/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/11/6325/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. T. L. Magnanti & R. T. Wong, 1984. "Network Design and Transportation Planning: Models and Algorithms," Transportation Science, INFORMS, vol. 18(1), pages 1-55, February.
    2. Farahani, Reza Zanjirani & Miandoabchi, Elnaz & Szeto, W.Y. & Rashidi, Hannaneh, 2013. "A review of urban transportation network design problems," European Journal of Operational Research, Elsevier, vol. 229(2), pages 281-302.
    3. Laporte, Gilbert & Mesa, Juan A. & Ortega, Francisco A., 2000. "Optimization methods for the planning of rapid transit systems," European Journal of Operational Research, Elsevier, vol. 122(1), pages 1-10, April.
    4. Ahmed, Leena & Mumford, Christine & Kheiri, Ahmed, 2019. "Solving urban transit route design problem using selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 274(2), pages 545-559.
    5. Lindau, Luis Antonio & Hidalgo, Dario & de Almeida Lobo, Adriana, 2014. "Barriers to planning and implementing Bus Rapid Transit systems," Research in Transportation Economics, Elsevier, vol. 48(C), pages 9-15.
    6. Laporte, G. & Mesa, J.A. & Ortega, F.A. & Perea, F., 2011. "Planning rapid transit networks," Socio-Economic Planning Sciences, Elsevier, vol. 45(3), pages 95-104, September.
    7. Sitti Asmah Hassan & Intan Nurfauzirah Shafiqah Hamzani & Abd. Ramzi Sabli & Nur Sabahiah Abdul Sukor, 2021. "Bus Rapid Transit System Introduction in Johor Bahru: A Simulation-Based Assessment," Sustainability, MDPI, vol. 13(8), pages 1-13, April.
    8. Guihaire, Valérie & Hao, Jin-Kao, 2008. "Transit network design and scheduling: A global review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(10), pages 1251-1273, December.
    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. Weckström, Christoffer & Mladenović, Miloš N. & Kujala, Rainer & Saramäki, Jari, 2021. "Navigability assessment of large-scale redesigns in nine public transport networks: Open timetable data approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 212-229.
    2. Tong, Lu & Zhou, Xuesong & Miller, Harvey J., 2015. "Transportation network design for maximizing space–time accessibility," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 555-576.
    3. Cancela, Héctor & Mauttone, Antonio & Urquhart, María E., 2015. "Mathematical programming formulations for transit network design," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 17-37.
    4. Jose L. Walteros & Andrés L. Medaglia & Germán Riaño, 2015. "Hybrid Algorithm for Route Design on Bus Rapid Transit Systems," Transportation Science, INFORMS, vol. 49(1), pages 66-84, February.
    5. Evert Vermeir & Javier Durán-Micco & Pieter Vansteenwegen, 2022. "The grid based approach, a fast local evaluation technique for line planning," 4OR, Springer, vol. 20(4), pages 603-635, December.
    6. Siying Zhu & Feng Zhu, 2020. "Multi-objective bike-way network design problem with space–time accessibility constraint," Transportation, Springer, vol. 47(5), pages 2479-2503, October.
    7. Christina Iliopoulou & Konstantinos Kepaptsoglou & Eleni Vlahogianni, 2019. "Metaheuristics for the transit route network design problem: a review and comparative analysis," Public Transport, Springer, vol. 11(3), pages 487-521, October.
    8. Javier Durán-Micco & Pieter Vansteenwegen, 2022. "A survey on the transit network design and frequency setting problem," Public Transport, Springer, vol. 14(1), pages 155-190, March.
    9. Javier Duran & Lorena Pradenas & Victor Parada, 2019. "Transit network design with pollution minimization," Public Transport, Springer, vol. 11(1), pages 189-210, June.
    10. Yin, Yong & Chen, Jinqu & Chen, Zhuo & Du, Bo & Li, Baowen, 2024. "A scenario model for enhancing the resilience of an urban rail transit network by adding new links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    11. Loder, Allister & Bliemer, Michiel C.J. & Axhausen, Kay W., 2022. "Optimal pricing and investment in a multi-modal city — Introducing a macroscopic network design problem based on the MFD," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 113-132.
    12. Abdulkerim Benli & İbrahim Akgün, 2023. "A Multi-Objective Mathematical Programming Model for Transit Network Design and Frequency Setting Problem," Mathematics, MDPI, vol. 11(21), pages 1-23, October.
    13. Arbex, Renato Oliveira & da Cunha, Claudio Barbieri, 2015. "Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 355-376.
    14. Liang, Jinpeng & Wu, Jianjun & Gao, Ziyou & Sun, Huijun & Yang, Xin & Lo, Hong K., 2019. "Bus transit network design with uncertainties on the basis of a metro network: A two-step model framework," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 115-138.
    15. David Canca & Belén Navarro-Carmona & Gabriel Villa & Alejandro Zarzo, 2023. "A Multilayer Network Approach for the Bimodal Bus–Pedestrian Line Planning Problem," Mathematics, MDPI, vol. 11(19), pages 1-36, October.
    16. Amirali Zarrinmehr & Mahmoud Saffarzadeh & Seyedehsan Seyedabrishami & Yu Marco Nie, 2016. "A path-based greedy algorithm for multi-objective transit routes design with elastic demand," Public Transport, Springer, vol. 8(2), pages 261-293, September.
    17. Hugo M. Repolho & António P. Antunes & Richard L. Church, 2013. "Optimal Location of Railway Stations: The Lisbon-Porto High-Speed Rail Line," Transportation Science, INFORMS, vol. 47(3), pages 330-343, August.
    18. Ahern, Zeke & Paz, Alexander & Corry, Paul, 2022. "Approximate multi-objective optimization for integrated bus route design and service frequency setting," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 1-25.
    19. Bagloee, Saeed Asadi & Sarvi, Majid & Wolshon, Brian & Dixit, Vinayak, 2017. "Identifying critical disruption scenarios and a global robustness index tailored to real life road networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 60-81.
    20. Elnaz Miandoabchi & Reza Farahani & W. Szeto, 2012. "Bi-objective bimodal urban road network design using hybrid metaheuristics," 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. 20(4), pages 583-621, December.

    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:11:p:6325-:d:567844. 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.