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Public transport vehicle scheduling featuring multiple vehicle types

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  • Hassold, Stephan
  • Ceder, Avishai (Avi)

Abstract

Vehicle scheduling is a crucial step of the public transport planning process because it results in the number of vehicles required, thus it is directly related to fixed cost and labor cost. It is desirable, therefore, to minimize the number of vehicles used and operational cost. This paper proposes a new methodology for the multiple vehicle types vehicle scheduling problem (MVT-VSP). The methodology is based on a minimum-cost network flow model utilizing sets of Pareto-optimal timetables for individual bus lines. Given a fixed fleet size the suggested methodology also allows a selection of the optimal timetable. The method developed enables to stipulate the use of a particular vehicle type for a trip or to allow for a substitution either by a larger vehicle or a combination of smaller vehicles with the same or higher total capacity. Moreover, a variation of the method portrayed makes it possible to construct sub-optimal timetables given a reduction of the vehicle-scheduling cost. It is demonstrated that a substitution of vehicles is beneficial and can lead to significant cost reductions in the range of more than 27%. The suggested methodology is applied to a real-life case study in Auckland, New Zealand, and the results show improvements of greater than 15% in terms of the cost of fleet compared with vehicle schedules that are provided by standard models.

Suggested Citation

  • Hassold, Stephan & Ceder, Avishai (Avi), 2014. "Public transport vehicle scheduling featuring multiple vehicle types," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 129-143.
  • Handle: RePEc:eee:transb:v:67:y:2014:i:c:p:129-143
    DOI: 10.1016/j.trb.2014.04.009
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    References listed on IDEAS

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    Cited by:

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    2. Chen, Zhiwei & Li, Xiaopeng & Zhou, Xuesong, 2019. "Operational design for shuttle systems with modular vehicles under oversaturated traffic: Discrete modeling method," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 1-19.
    3. Uçar, Ezgi & İlker Birbil, Ş. & Muter, İbrahim, 2017. "Managing disruptions in the multi-depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 249-269.
    4. Zhang, Wei & (Ato) Xu, Wangtu, 2017. "Simulation-based robust optimization for the schedule of single-direction bus transit route: The design of experiment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 203-230.
    5. Kulkarni, Sarang & Krishnamoorthy, Mohan & Ranade, Abhiram & Ernst, Andreas T. & Patil, Rahul, 2018. "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 457-487.
    6. Xuemei Zhou & Yehan Wang & Xiangfeng Ji & Caitlin Cottrill, 2019. "Coordinated Control Strategy for Multi-Line Bus Bunching in Common Corridors," Sustainability, MDPI, vol. 11(22), pages 1-23, November.
    7. Liu, Tao & (Avi) Ceder, Avishai, 2017. "Deficit function related to public transport: 50 year retrospective, new developments, and prospects," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 1-19.
    8. Harris, Andrew & Soban, Danielle & Smyth, Beatrice M. & Best, Robert, 2020. "A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies," Applied Energy, Elsevier, vol. 261(C).
    9. Liang Gong & Yinzhen Li & Dejie Xu, 2019. "Combinational Scheduling Model Considering Multiple Vehicle Sizes," Sustainability, MDPI, vol. 11(19), pages 1-14, September.
    10. Chen, Zhiwei & Li, Xiaopeng & Zhou, Xuesong, 2020. "Operational design for shuttle systems with modular vehicles under oversaturated traffic: Continuous modeling method," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 76-100.
    11. 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.
    12. Guedes, Pablo C. & Borenstein, Denis, 2018. "Real-time multi-depot vehicle type rescheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 217-234.
    13. 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.
    14. Gkiotsalitis, K. & Schmidt, M.E. & van der Hurk, E., 2021. "Subline frequency setting for autonomous minibusses under demand uncertainty," ERIM Report Series Research in Management ERS-2021-008-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    15. Shen, Yindong & Xu, Jia & Li, Jingpeng, 2016. "A probabilistic model for vehicle scheduling based on stochastic trip times," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 19-31.
    16. Shiqian Ji & Jiaming Zhong & Zhaocheng He, 2022. "A Bus Subsidy Scheme Design Model Considering Competition between Bus Companies," Sustainability, MDPI, vol. 14(7), pages 1-19, April.

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