IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0166064.html
   My bibliography  Save this article

Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System

Author

Listed:
  • Kah Huo Leong
  • Hamzah Abdul-Rahman
  • Chen Wang
  • Chiu Chuen Onn
  • Siaw-Chuing Loo

Abstract

Railway and metro transport systems (RS) are becoming one of the popular choices of transportation among people, especially those who live in urban cities. Urbanization and increasing population due to rapid development of economy in many cities are leading to a bigger demand for urban rail transit. Despite being a popular variant of Traveling Salesman Problem (TSP), it appears that the universal formula or techniques to solve the problem are yet to be found. This paper aims to develop an optimization algorithm for optimum route selection to multiple destinations in RS before returning to the starting point. Bee foraging behaviour is examined to generate a reliable algorithm in railway TSP. The algorithm is then verified by comparing the results with the exact solutions in 10 test cases, and a numerical case study is designed to demonstrate the application with large size sample. It is tested to be efficient and effective in railway route planning as the tour can be completed within a certain period of time by using minimal resources. The findings further support the reliability of the algorithm and capability to solve the problems with different complexity. This algorithm can be used as a method to assist business practitioners making better decision in route planning.

Suggested Citation

  • Kah Huo Leong & Hamzah Abdul-Rahman & Chen Wang & Chiu Chuen Onn & Siaw-Chuing Loo, 2016. "Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-24, December.
    • Handle: RePEc:plo:pone00:0166064
    DOI: 10.1371/journal.pone.0166064
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0166064
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0166064&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0166064?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Laporte, Gilbert, 1992. "The vehicle routing problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(3), pages 345-358, June.
    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. Juraj Čamaj & Eva Brumerčíková & Michal Petr Hranický, 2020. "Information System and Technology Optimization as a Tool for Ensuring the Competitiveness of a Railway Undertaking—Case Study," Sustainability, MDPI, vol. 12(21), pages 1-23, October.

    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. Gutierrez, Genaro J. & Kouvelis, Panagiotis & Kurawarwala, Abbas A., 1996. "A robustness approach to uncapacitated network design problems," European Journal of Operational Research, Elsevier, vol. 94(2), pages 362-376, October.
    2. Petersen, E. R. & Taylor, A. J., 2001. "An investment planning model for a new North-Central railway in Brazil," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(9), pages 847-862, November.
    3. Agarwal, Y.K. & Aneja, Y.P. & Jayaswal, Sachin, 2022. "Directed fixed charge multicommodity network design: A cutting plane approach using polar duality," European Journal of Operational Research, Elsevier, vol. 299(1), pages 118-136.
    4. Cipriani, Ernesto & Fusco, Gaetano, 2004. "Combined signal setting design and traffic assignment problem," European Journal of Operational Research, Elsevier, vol. 155(3), pages 569-583, June.
    5. Dessouky, Maged M & Shao, Yihuan E, 2017. "Routing Strategies for Efficient Deployment of Alternative Fuel Vehicles for Freight Delivery," Institute of Transportation Studies, Working Paper Series qt0nj024qn, Institute of Transportation Studies, UC Davis.
    6. Wu, Dexiang & Wu, Desheng Dash, 2020. "A decision support approach for two-stage multi-objective index tracking using improved lagrangian decomposition," Omega, Elsevier, vol. 91(C).
    7. Ortiz-Astorquiza, Camilo & Contreras, Ivan & Laporte, Gilbert, 2018. "Multi-level facility location problems," European Journal of Operational Research, Elsevier, vol. 267(3), pages 791-805.
    8. Lara, Cristiana L. & Koenemann, Jochen & Nie, Yisu & de Souza, Cid C., 2023. "Scalable timing-aware network design via lagrangian decomposition," European Journal of Operational Research, Elsevier, vol. 309(1), pages 152-169.
    9. Klaus Büdenbender & Tore Grünert & Hans-Jürgen Sebastian, 2000. "A Hybrid Tabu Search/Branch-and-Bound Algorithm for the Direct Flight Network Design Problem," Transportation Science, INFORMS, vol. 34(4), pages 364-380, November.
    10. Joseph Y. J. Chow & Amelia C. Regan, 2011. "Real Option Pricing of Network Design Investments," Transportation Science, INFORMS, vol. 45(1), pages 50-63, February.
    11. Rajeev Kumar, 2022. "A Gig Worker-Centric Approach for Efficient Picking and Delivery of Electric Scooters," International Journal of Business Analytics (IJBAN), IGI Global, vol. 9(1), pages 1-14, January.
    12. Nader Naderializadeh & Kevin A. Crowe, 2020. "Formulating the integrated forest harvest-scheduling model to reduce the cost of the road-networks," Operational Research, Springer, vol. 20(4), pages 2283-2306, December.
    13. Melkote, Sanjay & Daskin, Mark S., 2001. "Capacitated facility location/network design problems," European Journal of Operational Research, Elsevier, vol. 129(3), pages 481-495, March.
    14. Wang, Zujian & Qi, Mingyao, 2019. "Service network design considering multiple types of services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 1-14.
    15. 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.
    16. Yogesh Kumar Agarwal & Prahalad Venkateshan, 2019. "New Valid Inequalities for the Optimal Communication Spanning Tree Problem," INFORMS Journal on Computing, INFORMS, vol. 31(2), pages 268-284, April.
    17. Zvi Drezner & Said Salhi, 2002. "Using hybrid metaheuristics for the one‐way and two‐way network design problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(5), pages 449-463, August.
    18. Grunert, Tore & Sebastian, Hans-Jurgen, 2000. "Planning models for long-haul operations of postal and express shipment companies," European Journal of Operational Research, Elsevier, vol. 122(2), pages 289-309, April.
    19. Ospina, Juan P. & Duque, Juan C. & Botero-Fernández, Verónica & Montoya, Alejandro, 2022. "The maximal covering bicycle network design problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 222-236.
    20. Almoustafa, Samira & Hanafi, Said & Mladenović, Nenad, 2013. "New exact method for large asymmetric distance-constrained vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 226(3), pages 386-394.

    More about this item

    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:plo:pone00:0166064. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.