IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i17p11097-d907291.html
   My bibliography  Save this article

A Heuristic Algorithm Based on Travel Demand for Transit Network Design

Author

Listed:
  • Yuan Liu

    (College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China)

  • Heshan Zhang

    (College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China)

  • Tao Xu

    (College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China)

  • Yaping Chen

    (Department of Civil Engineering Design, Chongqing Architectural Design Limited Company, Chongqing 401122, China)

Abstract

This study proposes a simultaneous optimization model that considers flow assignment and vehicle capacity for the problem of transit network design to determine the route structure and frequencies simultaneously. The problem is focused on reducing the total travel time and the number of transfers. A heuristic algorithm is developed to solve this problem. In the proposed algorithm, the initial routes are generated according to a changing demand matrix, which can reflect the real-time demand with transfers and ensure that the direction of route generation maximizes the percentage of direct service. A regulating method for a sequence of stops is used during route generation to guarantee the shortest trip time for a formed route. Vehicles are allocated to each route according to the flow share. The concept of vehicle difference is introduced to evaluate the distinction between actual allocated vehicles and required vehicles for each route. The optimization process of frequencies based on vehicle difference can ensure that the solution meets the constraints. Two scale networks are used to illustrate the performances of the proposed method. Results show that route structure and frequencies can be optimized simultaneously through the proposed method. Different scenarios are created to test the algorithm properties via various parameter values. The test result indicates that the upper bound is a key parameter to balance the proportion of direct service and average in-vehicle travel time (AIVTT), and the increased number of planning routes can improve the proportion of direct service.

Suggested Citation

  • Yuan Liu & Heshan Zhang & Tao Xu & Yaping Chen, 2022. "A Heuristic Algorithm Based on Travel Demand for Transit Network Design," Sustainability, MDPI, vol. 14(17), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:11097-:d:907291
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/17/11097/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/17/11097/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. G. F. Newell, 1971. "Dispatching Policies for a Transportation Route," Transportation Science, INFORMS, vol. 5(1), pages 91-105, February.
    2. Zhi-Chun Li & William Lam & S. Wong, 2009. "The Optimal Transit Fare Structure under Different Market Regimes with Uncertainty in the Network," Networks and Spatial Economics, Springer, vol. 9(2), pages 191-216, June.
    3. de Palma, André & Lindsey, Robin, 2001. "Optimal timetables for public transportation," Transportation Research Part B: Methodological, Elsevier, vol. 35(8), pages 789-813, September.
    4. Hadas, Yuval & Shnaiderman, Matan, 2012. "Public-transit frequency setting using minimum-cost approach with stochastic demand and travel time," Transportation Research Part B: Methodological, Elsevier, vol. 46(8), pages 1068-1084.
    5. Tétreault, Paul R. & El-Geneidy, Ahmed M., 2010. "Estimating bus run times for new limited-stop service using archived AVL and APC data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(6), pages 390-402, July.
    6. Szeto, W.Y. & Jiang, Y., 2014. "Transit route and frequency design: Bi-level modeling and hybrid artificial bee colony algorithm approach," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 235-263.
    7. Gao, Ziyou & Sun, Huijun & Shan, Lian Long, 2004. "A continuous equilibrium network design model and algorithm for transit systems," Transportation Research Part B: Methodological, Elsevier, vol. 38(3), pages 235-250, March.
    8. Zhengfeng Huang & Gang Ren & Haixu Liu, 2013. "Optimizing Bus Frequencies under Uncertain Demand: Case Study of the Transit Network in a Developing City," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-10, May.
    9. Nguyen, S. & Pallottino, S., 1988. "Equilibrium traffic assignment for large scale transit networks," European Journal of Operational Research, Elsevier, vol. 37(2), pages 176-186, November.
    10. Martin Desrochers & François Soumis, 1989. "A Column Generation Approach to the Urban Transit Crew Scheduling Problem," Transportation Science, INFORMS, vol. 23(1), pages 1-13, February.
    11. Asadi Bagloee, Saeed & Ceder, Avishai (Avi), 2011. "Transit-network design methodology for actual-size road networks," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1787-1804.
    12. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2004. "Scheduling multimodal transportation systems," European Journal of Operational Research, Elsevier, vol. 155(3), pages 603-615, June.
    13. Alan Murray, 2003. "A Coverage Model for Improving Public Transit System Accessibility and Expanding Access," Annals of Operations Research, Springer, vol. 123(1), pages 143-156, October.
    14. Chen, Jingxu & Liu, Zhiyuan & Zhu, Senlai & Wang, Wei, 2015. "Design of limited-stop bus service with capacity constraint and stochastic travel time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 1-15.
    15. Rachel C. W. Wong & Tony W. Y. Yuen & Kwok Wah Fung & Janny M. Y. Leung, 2008. "Optimizing Timetable Synchronization for Rail Mass Transit," Transportation Science, INFORMS, vol. 42(1), pages 57-69, February.
    16. Szeto, W.Y. & Wu, Yongzhong, 2011. "A simultaneous bus route design and frequency setting problem for Tin Shui Wai, Hong Kong," European Journal of Operational Research, Elsevier, vol. 209(2), pages 141-155, March.
    17. Lam, W. H. K. & Gao, Z. Y. & Chan, K. S. & Yang, H., 1999. "A stochastic user equilibrium assignment model for congested transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 33(5), pages 351-368, June.
    18. LeBlanc, Larry J., 1988. "Transit system network design," Transportation Research Part B: Methodological, Elsevier, vol. 22(5), pages 383-390, October.
    19. Joaquín de Cea & Enrique Fernández, 1993. "Transit Assignment for Congested Public Transport Systems: An Equilibrium Model," Transportation Science, INFORMS, vol. 27(2), pages 133-147, May.
    20. Mandl, Christoph E., 1980. "Evaluation and optimization of urban public transportation networks," European Journal of Operational Research, Elsevier, vol. 5(6), pages 396-404, December.
    21. Ceder, A. & Golany, B. & Tal, O., 2001. "Creating bus timetables with maximal synchronization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(10), pages 913-928, December.
    22. Ceder, Avishai & Wilson, Nigel H. M., 1986. "Bus network design," Transportation Research Part B: Methodological, Elsevier, vol. 20(4), pages 331-344, August.
    23. Enrique Fernandez & Patrice Marcotte, 1992. "Operators-Users Equilibrium Model in a Partially Regulated Transit System," Transportation Science, INFORMS, vol. 26(2), pages 93-105, May.
    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. Xudong Diao & Ai Gao & Xin Jin & Hui Chen, 2022. "A Layer-Based Relaxation Approach for Service Network Design," Sustainability, MDPI, vol. 14(20), pages 1-13, October.
    2. Andrea Gemma & Ernesto Cipriani & Umberto Crisalli & Livia Mannini & Marco Petrelli, 2024. "A Bus Network Design Model under Demand Variation: A Case Study of the Management of Rome’s Bus Network," Sustainability, MDPI, vol. 16(2), pages 1-13, January.

    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. Ibarra-Rojas, O.J. & Delgado, F. & Giesen, R. & Muñoz, J.C., 2015. "Planning, operation, and control of bus transport systems: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 38-75.
    2. Szeto, W.Y. & Jiang, Y., 2014. "Transit route and frequency design: Bi-level modeling and hybrid artificial bee colony algorithm approach," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 235-263.
    3. Tian, Qingyun & Wang, David Z.W. & Lin, Yun Hui, 2021. "Service operation design in a transit network with congested common lines," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 81-102.
    4. 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.
    5. 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.
    6. Ren, Hualing & Song, Yingjie & Long, Jiancheng & Si, Bingfeng, 2021. "A new transit assignment model based on line and node strategies," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 121-142.
    7. 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.
    8. Elnaz Miandoabchi & Reza Farahani & Wout Dullaert & W. Szeto, 2012. "Hybrid Evolutionary Metaheuristics for Concurrent Multi-Objective Design of Urban Road and Public Transit Networks," Networks and Spatial Economics, Springer, vol. 12(3), pages 441-480, September.
    9. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.
    10. Du, Muqing & Chen, Anthony, 2022. "Sensitivity analysis for transit equilibrium assignment and applications to uncertainty analysis," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 175-202.
    11. Philipp Heyken Soares, 2021. "Zone-based public transport route optimisation in an urban network," Public Transport, Springer, vol. 13(1), pages 197-231, March.
    12. Martínez, Héctor & Mauttone, Antonio & Urquhart, María E., 2014. "Frequency optimization in public transportation systems: Formulation and metaheuristic approach," European Journal of Operational Research, Elsevier, vol. 236(1), pages 27-36.
    13. 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.
    14. Tian, Qingyun & Wang, David Z.W. & Lin, Yun Hui, 2022. "Optimal deployment of autonomous buses into a transit service network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    15. 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.
    16. Wu, Weitiao & Liu, Ronghui & Jin, Wenzhou & Ma, Changxi, 2019. "Stochastic bus schedule coordination considering demand assignment and rerouting of passengers," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 275-303.
    17. Dakic, Igor & Yang, Kaidi & Menendez, Monica & Chow, Joseph Y.J., 2021. "On the design of an optimal flexible bus dispatching system with modular bus units: Using the three-dimensional macroscopic fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 148(C), pages 38-59.
    18. Manser, Patrick & Becker, Henrik & Hörl, Sebastian & Axhausen, Kay W., 2020. "Designing a large-scale public transport network using agent-based microsimulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 1-15.
    19. Weiya Chen & Xin Liu & Dingfang Chen & Xin Pan, 2019. "Setting Headways on a Bus Route under Uncertain Conditions," Sustainability, MDPI, vol. 11(10), pages 1-13, May.
    20. Suman, Hemant & Larrain, Homero & Muñoz, Juan Carlos, 2021. "The impact of using a naïve approach in the limited-stop bus service design problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 45-61.

    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:17:p:11097-:d:907291. 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.