DOI QR코드

DOI QR Code

Non-periodic Subway Scheduling that Minimizes Operational Cost and Passenger Waiting Time

  • Hong, YunWoo (Yonsei School of Business, Yonsei University) ;
  • Chung, Yerim (Yonsei School of Business, Yonsei University) ;
  • Min, YunHong (Graduate School of Logistics, Incheon National University)
  • Received : 2018.07.09
  • Accepted : 2018.08.20
  • Published : 2018.08.31

Abstract

Subway metro scheduling is one of the most important problems impacting passenger convenience today. To operate efficiently, the Seoul metro uses regular, periodic schedules for all lanes, both north and southbound. However, many past studies suggest that non-periodic scheduling would better optimize costs. Since the Seoul metro is continuously facing a deficit, adopting a non-periodic schedule may be necessary. Two objectives are presented; the first, to minimize the average passengers' waiting time, and the second, to minimize total costs, the sum of the passenger waiting time, and the operational costs. In this paper, we use passenger smart card data and a precise estimation of transfer times. To find the optimal time-table, a genetic algorithm is used to find the best solution for both objectives. Using Python 3.5 for the analysis, for the first objective, we are able to reduce the average waiting time, even when there are fewer trains. For the second objective, we are able to save about 4.5 thousand USD with six fewer trains.

Keywords

References

  1. Homepage of Seoul Metro Traffic Center: http://www.seo ulmetro.co.kr/
  2. Homepage of Seoul Statistics: http://stat.seoul.go.kr/
  3. ,2017.01.01., http://news.mt.co.kr/mtv iew.php?no=2016122314260651864&outlink=1&ref=
  4. E. Barrena, D. Canca, L.C. Coelho and G. Laporte, "Single-line rail rapid transit timetabling under dynamic Passenger demand", Transportation Research Part B, Vol. 70, pp. 134-150, 2014. https://doi.org/10.1016/j.trb.2014.08.013
  5. K.S. Kwon, "Development and Application of Operating Cost Function of Seoul Subway with Partial-Allocation Method", Thesis for Master's Degree. Department of Transportation Engineering, Hanyang University, 2001.
  6. G.F. Newell, G F, "Dispatching policies for a transportation route", Transportation Science, Vol. 5, No. 1, pp. 91-105, 1971. https://doi.org/10.1287/trsc.5.1.91
  7. J.F. Guan, H. Yang and S.C. Wirasinghe, "Simultaneous optimization of transit line configuration and passenger line assignment", Transportation Research Part B: Methodological, Vol. 40, No. 10, pp. 885-902, 2006. https://doi.org/10.1016/j.trb.2005.12.003
  8. W.O. Assis, and B.E. Milani, "Generation of optimal schedules for metro lines using model predictive control", Automatica, Vol. 40, No. 8, pp. 1397-1404, 2004. https://doi.org/10.1016/j.automatica.2004.02.021
  9. J.P. Li, "Train station passenger flow study", In Simulation Conference, 2000. Proceedings. Winter 2, IEEE, pp. 1173-1176, 2000.
  10. J. Hu, X. Shi, J. Song and Y. Xu, "Optimal design for urban mass transit network based on evolutionary algorithms", In L Wang, K Chen and Y S Ong (Eds.), Advances in Natural Computation, pp. 1089-1100. Springer: Berlin Heidelberg, 2005.
  11. H. Niu, and X. Zhou, "Optimizing urban rail timetable under time-dependent demand and oversaturated conditions", Transportation Research Part C: Emerging Technologies, Vol. No. 36, pp. 212-230, 2013.
  12. F. Zhao, and X. Zeng, "Optimization of transit route network, vehicle headways and timetables for large-scale transit networks", European Journal of Operational Research, Vol. 186, No. 2, pp. 841-855, 2008. https://doi.org/10.1016/j.ejor.2007.02.005
  13. R.C. Wong, and J.M. Leung, "Timetable synchronization for mass transit railway", In Proceedings of the 9th International Conference on Computer-Aided Scheduling of Public Transport (CASPT), August, 2004.
  14. X. Feng, X. Wang and H. Zhang, "Passenger transfer efficiency optimization modelling research with simulations", International Journal of Simulation Modelling, (IJSIMM), Vol. 13, No. 2, pp. 210-218, 2014. https://doi.org/10.2507/IJSIMM13(2)CO7
  15. V. Poorjafari, W.L. Yue, and N. Holyoak, "A comparison between genetic algorithms and simulated annealing for minimizing transfer waiting time in transit systems", International Journal of Engineering and Technology, Vol. 8, No. 3, pp. 216-221, 2015. https://doi.org/10.7763/IJET.2016.V6.888
  16. S.P. Hong, Y.H. Min, M.J. Park, K.M. Kim and S.M. Oh, "Precise estimation of connections of metro passengers from Smart Card data", Transportation, Vol. 43, No. 5, pp. 749-769, 2016. https://doi.org/10.1007/s11116-015-9617-y
  17. J.S. Park, and K.S. Lee, "Analysis of passenger flows in the subway transportation network of the metropolitan Seoul", Journal of KIISE: Computing Practices and Letters, Vol. 16, No. 3, pp. 316-323, 2010.
  18. S.G. Shin, Y. Cho, and C. Lee, "Integrated transit service evaluation methodologies using transportation card data", Technical Report 2007, Seoul Development Institute, 2007.
  19. E.Y. Cho, "Changes of walking pattern to walking determinants in pedestrians of urban streets", Thesis for Master's Degree. Department of Sports Industry, Kookmin University, 2009.
  20. J.S. Kim, "Calculation model of walking access time for the estimation of the catchment area of the subway", Thesis for Master's Degree. Department of Urban Engineering, University of Seoul, 2016.
  21. C. Rongwu, Y. Tao, and B.R. Bisrat, "A genetic algorithm based train speed regulation optimization", WIT Transactions on The Built Environment, Vol. 135, pp. 791-802, 2014.
  22. , 2015.01.28., http://www.experian.co.uk/bl ogs/latest-thinking/how-long-are-customers-willing -to-wait/