IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i23p6531-d288784.html
   My bibliography  Save this article

Optimization of a Bikeway Network with Selective Nodes

Author

Listed:
  • C. S. Shui

    (Department of Transportation and Logistics Management, The National Chiao Tung University, Hsinchu City 300, Taiwan)

  • W. L. Chan

    (Department of Civil Engineering, The University of Hong Kong, Hong Kong)

Abstract

Setting up a bikeway network has been recognized as one of the most effective measures to motivate cycling. In fact, a highly connected, exclusive bikeway network that covers all demand sources can be an attractive and time-saving measure, but it requires very high setup costs. The planner often needs to have a trade-off between demand coverage and travel time under a given construction cost. This paper introduces a novel bikeway design problem which determines an optimal bikeway network that covers all potential cycling demand sources with minimal total travel time and under budget constraints. In the context of designing a bike sharing system, the resultant node set of the bikeway network can be interpreted as the locations of the shared bike stations which can cover all cycling demands. A two-stage solution method, by combining the genetic algorithm and a novel elimination heuristic, is proposed to solve the problem by firstly determining the subset of nodes (selected nodes) that can cover all the demand sources and then designing the bikeway network that connects all selected nodes within a given budget. Numerical studies illustrate the advantages of elimination heuristics in solving the proposed problem and the effect of the budget towards the solution fitness with or without a solution. Case studies of two proposed new towns in Hong Kong are provided to illustrate the applicability and effectiveness of the method in bikeway design. This optimization model can be applied to bike-sharing system design problems which aims to cover all demand sources by providing bike stations that are also well connected with exclusive bikeways subject to budget constraints.

Suggested Citation

  • C. S. Shui & W. L. Chan, 2019. "Optimization of a Bikeway Network with Selective Nodes," Sustainability, MDPI, vol. 11(23), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:23:p:6531-:d:288784
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/23/6531/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/23/6531/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Frade, Ines & Ribeiro, Anabela, 2015. "Bike-sharing stations: A maximal covering location approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 216-227.
    2. Sohn, Keemin, 2011. "Multi-objective optimization of a road diet network design," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 499-511, July.
    3. Lin, Jenn-Rong & Yang, Ta-Hui, 2011. "Strategic design of public bicycle sharing systems with service level constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(2), pages 284-294, March.
    4. Majumdar, Bandhan Bandhu & Mitra, Sudeshna, 2018. "Analysis of bicycle route-related improvement strategies for two Indian cities using a stated preference survey," Transport Policy, Elsevier, vol. 63(C), pages 176-188.
    5. Elliot Fishman & Simon Washington & Narelle Haworth, 2013. "Bike Share: A Synthesis of the Literature," Transport Reviews, Taylor & Francis Journals, vol. 33(2), pages 148-165, March.
    6. Ralph Buehler & Jennifer Dill, 2016. "Bikeway Networks: A Review of Effects on Cycling," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 9-27, 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. Jonas Schmid-Querg & Andreas Keler & Georgios Grigoropoulos, 2021. "The Munich Bikeability Index: A Practical Approach for Measuring Urban Bikeability," Sustainability, MDPI, vol. 13(1), pages 1-14, January.
    2. Jacek Oskarbski & Krystian Birr & Karol Żarski, 2021. "Bicycle Traffic Model for Sustainable Urban Mobility Planning," Energies, MDPI, vol. 14(18), pages 1-36, September.

    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. Mix, Richard & Hurtubia, Ricardo & Raveau, Sebastián, 2022. "Optimal location of bike-sharing stations: A built environment and accessibility approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 126-142.
    2. Nigro, Marialisa & Castiglione, Marisdea & Maria Colasanti, Fabio & De Vincentis, Rosita & Valenti, Gaetano & Liberto, Carlo & Comi, Antonio, 2022. "Exploiting floating car data to derive the shifting potential to electric micromobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 78-93.
    3. Çelebi, Dilay & Yörüsün, Aslı & Işık, Hanife, 2018. "Bicycle sharing system design with capacity allocations," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 86-98.
    4. Jessica Berg & Malin Henriksson & Jonas Ihlström, 2019. "Comfort First! Vehicle-Sharing Systems in Urban Residential Areas: The Importance for Everyday Mobility and Reduction of Car Use among Pilot Users," Sustainability, MDPI, vol. 11(9), pages 1-16, April.
    5. Wu, Chunliang & Kim, Inhi, 2020. "Analyzing the structural properties of bike-sharing networks: Evidence from the United States, Canada, and China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 52-71.
    6. Dehdari Ebrahimi, Zhila & Momenitabar, Mohsen & Nasri, Arefeh A. & Mattson, Jeremy, 2022. "Using a GIS-based spatial approach to determine the optimal locations of bikeshare stations: The case of Washington D.C," Transport Policy, Elsevier, vol. 127(C), pages 48-60.
    7. Hyungkyoo Kim, 2020. "Seasonal Impacts of Particulate Matter Levels on Bike Sharing in Seoul, South Korea," IJERPH, MDPI, vol. 17(11), pages 1-17, June.
    8. Mete Suleyman & Cil Zeynel Abidin & Özceylan Eren, 2018. "Location and Coverage Analysis of Bike- Sharing Stations in University Campus," Business Systems Research, Sciendo, vol. 9(2), pages 80-95, July.
    9. Bruno Albert Neumann-Saavedra & Teodor Gabriel Crainic & Bernard Gendron & Dirk Christian Mattfeld & Michael Römer, 2020. "Integrating Resource Management in Service Network Design for Bike-Sharing Systems," Transportation Science, INFORMS, vol. 54(5), pages 1251-1271, September.
    10. Elżbieta Macioszek & Paulina Świerk & Agata Kurek, 2020. "The Bike-Sharing System as an Element of Enhancing Sustainable Mobility—A Case Study based on a City in Poland," Sustainability, MDPI, vol. 12(8), pages 1-29, April.
    11. Xize Wang & Greg Lindsey & Jessica E. Schoner & Andrew Harrison, 2022. "Modeling Bike Share Station Activity: Effects of Nearby Businesses and Jobs on Trips to and from Stations," Papers 2207.10577, arXiv.org.
    12. Bullrich, Ignacio Tomás, 2021. "Estudio de viabilidad acerca de la instalación de un sistema de bikesharing en la ciudad de Mar del Plata," Nülan. Deposited Documents 3554, Universidad Nacional de Mar del Plata, Facultad de Ciencias Económicas y Sociales, Centro de Documentación.
    13. Albiński, Szymon & Fontaine, Pirmin & Minner, Stefan, 2018. "Performance analysis of a hybrid bike sharing system: A service-level-based approach under censored demand observations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 59-69.
    14. Chen, Qingxin & Ma, Shoufeng & Li, Hongming & Zhu, Ning & He, Qiao-Chu, 2024. "Optimizing bike rebalancing strategies in free-floating bike-sharing systems: An enhanced distributionally robust approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    15. Wang, Mingshu & Zhou, Xiaolu, 2017. "Bike-sharing systems and congestion: Evidence from US cities," Journal of Transport Geography, Elsevier, vol. 65(C), pages 147-154.
    16. Song, Jiatong & Li, Baicheng & Szeto, W.Y. & Zhan, Xingbin, 2024. "A station location design problem in a bike-sharing system with both conventional and electric shared bikes considering bike users’ roaming delay costs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    17. Yang, Lin & Zhang, Fayong & Kwan, Mei-Po & Wang, Ke & Zuo, Zejun & Xia, Shaotian & Zhang, Zhiyong & Zhao, Xinpei, 2020. "Space-time demand cube for spatial-temporal coverage optimization model of shared bicycle system: A study using big bike GPS data," Journal of Transport Geography, Elsevier, vol. 88(C).
    18. Park, Chung & Sohn, So Young, 2017. "An optimization approach for the placement of bicycle-sharing stations to reduce short car trips: An application to the city of Seoul," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 154-166.
    19. Caggiani, Leonardo & Camporeale, Rosalia & Marinelli, Mario & Ottomanelli, Michele, 2019. "User satisfaction based model for resource allocation in bike-sharing systems," Transport Policy, Elsevier, vol. 80(C), pages 117-126.
    20. Josep Maria Salanova & Georgia Ayfantopoulou & Evripidis Magkos & Ioannis Mallidis & Zisis Maleas & Santhanakrishnan Narayanan & Constantinos Antoniou & Athina Tympakianaki & Ignacio Martin & Jenny Fa, 2022. "Developing a Multilevel Decision Support Tool for Urban Mobility," Sustainability, MDPI, vol. 14(13), pages 1-19, June.

    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:11:y:2019:i:23:p:6531-:d:288784. 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.