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School bus routing problem in the stochastic and time-dependent transportation network

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  • Shichao Sun
  • Zhengyu Duan
  • Qi Xu

Abstract

Accidents, bad weathers, traffic congestions, etc. led to the uncertainties of travel times in real-life road networks, which greatly affected the quality of individual’s life and the reliability of transportation system. This paper addressed the school bus routing problem in such a stochastic and time-dependent road environment. Firstly, the problem was set based on a single-school configuration, and the students were picked up at their homes, which was in line with the current situation of school bus systems in China. Thus, it could be regarded as an independent problem of school bus route generation in random dynamic networks, which could be solved as a variant of extended Vehicle Routing Problem. However, due to the fluctuation and uncertainty of link travel times, the arrival time at each stop including the destination was varying. Therefore, the selection of optimal path connecting the current service node with the next one was treated as a sub-problem in this study, where the reliability of travel times in the stochastic and time-varying network was highly concerned by such time-rigid commuters. To this end, a Robust Optimal Schedule Times model with a hard time windows constraint was built to generate a most cost-reliable route for school buses. By the use of Robust Optimization method, it was intended to minimize the worst-case total cost which combined the cost of earlier schedule delays with the disutility of travel times. It was also proved that the proposed model could be converted into solving a conventional problem in deterministic dynamic networks for a reduction of computation complexity, which provided the potential of applying to the practical problems. Finally, the validity of the proposed model and its performance evaluation was analyzed through a small-scale computational instance, where all the link travel times in the simulated network were attributed to both time-varying and stochastic. Then, a mathematical programming solver was used to find the exact optimal solution. The results indicated that the model was valid, and the necessity of considering the stochastic and time-dependent nature of transportation networks was also confirmed in the case study.

Suggested Citation

  • Shichao Sun & Zhengyu Duan & Qi Xu, 2018. "School bus routing problem in the stochastic and time-dependent transportation network," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-17, August.
    • Handle: RePEc:plo:pone00:0202618
    DOI: 10.1371/journal.pone.0202618
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    References listed on IDEAS

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    1. T Bektaş & Seda Elmastaş, 2007. "Solving school bus routing problems through integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1599-1604, December.
    2. M. Spada & M. Bierlaire & Th. M. Liebling, 2005. "Decision-Aiding Methodology for the School Bus Routing and Scheduling Problem," Transportation Science, INFORMS, vol. 39(4), pages 477-490, November.
    3. Hernan Caceres & Rajan Batta & Qing He, 2017. "School Bus Routing with Stochastic Demand and Duration Constraints," Transportation Science, INFORMS, vol. 51(4), pages 1349-1364, November.
    4. Prakash, A. Arun, 2018. "Pruning algorithm for the least expected travel time path on stochastic and time-dependent networks," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 127-147.
    5. Schittekat, Patrick & Kinable, Joris & Sörensen, Kenneth & Sevaux, Marc & Spieksma, Frits & Springael, Johan, 2013. "A metaheuristic for the school bus routing problem with bus stop selection," European Journal of Operational Research, Elsevier, vol. 229(2), pages 518-528.
    6. Park, Junhyuk & Tae, Hyunchul & Kim, Byung-In, 2012. "A post-improvement procedure for the mixed load school bus routing problem," European Journal of Operational Research, Elsevier, vol. 217(1), pages 204-213.
    7. Ban, Xuegang (Jeff) & Pang, Jong-Shi & Liu, Henry X. & Ma, Rui, 2012. "Continuous-time point-queue models in dynamic network loading," Transportation Research Part B: Methodological, Elsevier, vol. 46(3), pages 360-380.
    8. Sam R. Thangiah & Adel Fergany & Bryan Wilson & Anthony Pitluga & William Mennell, 2008. "School Bus Routing in Rural School Districts," Lecture Notes in Economics and Mathematical Systems, in: Mark Hickman & Pitu Mirchandani & Stefan Voß (ed.), Computer-aided Systems in Public Transport, pages 209-232, Springer.
    9. Park, Junhyuk & Kim, Byung-In, 2010. "The school bus routing problem: A review," European Journal of Operational Research, Elsevier, vol. 202(2), pages 311-319, April.
    10. Ma, Rui & Ban, Xuegang (Jeff) & Pang, Jong-Shi, 2014. "Continuous-time dynamic system optimum for single-destination traffic networks with queue spillbacks," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 98-122.
    11. Joaquín Pacheco & Rafael Caballero & Manuel Laguna & Julián Molina, 2013. "Bi-Objective Bus Routing: An Application to School Buses in Rural Areas," Transportation Science, INFORMS, vol. 47(3), pages 397-411, August.
    12. Ellegood, William A. & Campbell, James F. & North, Jeremy, 2015. "Continuous approximation models for mixed load school bus routing," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 182-198.
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    Cited by:

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    4. Ellegood, William A. & Solomon, Stanislaus & North, Jeremy & Campbell, James F., 2020. "School bus routing problem: Contemporary trends and research directions," Omega, Elsevier, vol. 95(C).

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