Skip to main navigation menu Skip to main content Skip to site footer
Journal of Modern Mechanical Engineering and Technology

Articles

Vol. 10 (2023)

Profit-oriented High-speed Railway Network Line Planning with Capacity Limitations

DOI
https://doi.org/10.31875/2409-9848.2023.10.8
Submitted
June 2, 2023
Published
2023-06-03

Abstract

Abstract: Line planning is the transportation service's fundamental, which directly affects the subsequent operation plans. It is better to focus on the operational profit when considering the market competition for transportation operation plans. This paper aims to maximize the operational profit when optimizing the high-speed railway network line plan by constructing a mixed integer nonlinear programming model. The model integrates line planning and passenger route choice behaviors. An adaptive simulated annealing algorithm with neighborhood search is applied based on a given line pool. A heuristic passenger assignment method is developed to ensure a high level of passenger satisfaction. The proposed model and algorithm are experimentally evaluated. The instance results show that the operational profit and capacity utilization can be significantly improved. Compared with the designed greedy heuristic algorithm, the proposed algorithm performs better in operational profit improvement and has high efficiency.

References

  1. Wang Y, Peng Q Y, Liu L, et al. Optimization of High-Speed Railway Line Planning Considering Extra-Long Distance Transportation. J. Adv. Transp. 2020. https://doi.org/10.1155/2020/3062891
  2. Zhao S, Wu R, Shi F. A line planning approach for high-speed railway network with time-varying demand. Comput. Ind. Eng., 2021, 160: 107547. https://doi.org/10.1016/j.cie.2021.107547
  3. Jia L, Meng X, Qin Y. Line Planning in Emergencies for Railway Network. In: Train Operation in Emergencies. Advances in High-speed Rail Technology. 2017: 59-74, Springer, Singapore. https://doi.org/10.1007/978-981-10-4597-4_5
  4. Tian H, Shuai M, Li K. Optimization study of line planning for high speed railway based on an improved multi-objective differential evolution algorithm. IEEE Access, 2019; 7: 137731-137743. https://doi.org/10.1109/ACCESS.2019.2939483
  5. Park B H, Kim C S, Rho H L. On the railway line planning models considering the various halting patterns. World Congress on Engineering 2012. July 4-6, 2012. London, UK. International Association of Engineers, 2010; 2182: 2146-2151.
  6. Lv H, Pu S, Wang Y. Model and Algorithm for High-Speed Railway Line Planning. ICLEM 2014: System Planning, Supply Chain Management, and Safety. 2014: 280-285. https://doi.org/10.1061/9780784413753.042
  7. Pu S, Zhan S. Two-stage robust railway line-planning approach with passenger demand uncertainty. Transp. Res. Pt. e-Logist. Transp. Rev. 2021; 152: 102372. https://doi.org/10.1016/j.tre.2021.102372
  8. Lee C and Nair R. Robust transit line planning based on demand estimates obtained from mobile phones. EURO Journal on Transportation and Logistics, 10, 100034. https://doi.org/10.1016/j.ejtl.2021.100034
  9. Szeto W Y. and Jiang Y. Transit route and frequency design: Bi-level modeling and hybrid artificial bee colony algorithm approach. Transportation Research Part B: Methodological, 67: 235-263.
  10. https://doi.org/10.1016/j.trb.2014.05.008
  11. Su H, Tao W, Hu X. A line planning approach for high-speed rail networks with time-dependent demand and capacity constraints. Math. Probl. Eng., 2019. https://doi.org/10.1155/2019/7509586
  12. Schöbel A. Line planning in public transportation: models and methods. OR spectrum, 2012; 34(3): 491-510. https://doi.org/10.1007/s00291-011-0251-6
  13. Claessens M T, van Dijk N M, Zwaneveld P J. Cost optimal allocation of rail passenger lines. Eur. J. Oper. Res., 1998; 110(3): 474-489. https://doi.org/10.1016/S0377-2217(97)00271-3
  14. Bussieck M R, Lindner T, Lübbecke M E. A fast algorithm for near cost optimal line plans. Math. Method Oper. Res., 2004; 59(2): 205-220. https://doi.org/10.1007/s001860300332
  15. Goossens J W, van Hoesel S, Kroon L. On solving multi-type railway line planning problems. Eur. J. Oper. Res., 2006; 168(2): 403-424. https://doi.org/10.1016/j.ejor.2004.04.036
  16. Bussieck M R, Kreuzer P, Zimmermann U T. Optimal lines for railway systems. Eur. J. Oper. Res. 1997; 96(1): 54-63. https://doi.org/10.1016/0377-2217(95)00367-3
  17. Schöbel A, Scholl S. Line planning with minimal traveling time. In Proc., 5th Workshop on Algorithmic Methods and Models for Optimization of Railways (ATMOS'05). Schloss Dagstuhl-Leibniz-Zentrum für Informatik, 2006.
  18. Scholl S. Customer-oriented line planning. Dissertation. de. Verlag im Internet GmbH, 2006 Zugl.: Kaiserslautern, Techn. Univ., Diss., 2005. http://num.math.uni-goettingen.de/picap/pdf/E582.pdf.
  19. Pfetsch M E, Borndörfer R. Routing in Line Planning for Public Transport. In Operations Research Proceedings 2005. Springer, Berlin, Heidelberg, 2006; 405-410. https://doi.org/10.1007/3-540-32539-5_64
  20. Yan F, Goverde R M. Combined line planning and train timetabling for strongly heterogeneous railway lines with direct connections. Transp. Res. Pt. B-Methodol 2019; 127: 20-46. https://doi.org/10.1016/j.trb.2019.06.010
  21. Canca D, De-Los-Santos A, Laporte G et al. An adaptive neighborhood search metaheuristic for the integrated railway rapid transit network design and line planning problem. Comput. Oper. Res., 2017; 78: 1-14. https://doi.org/10.1016/j.cor.2016.08.008
  22. Canca D, De-Los-Santos A, Laporte G et al. Integrated railway rapid transit network design and line planning problem with maximum profit. Transp. Res. Pt. e-Logist. Transp. Rev., 2019; 127: 1-30. https://doi.org/10.1016/j.tre.2019.04.007
  23. Mao Z, Nie L, Yuan W et al. Profit-Oriented Railway Passenger Transportation Scheduling: An Integration Model of Line Planning and Ticket allocation. In Proc., 19th COTA International Conf. of Transportation, 2019: 1936-1948. https://doi.org/10.1061/9780784482292.169
  24. Liu D, Durán Micco J, Lu G, et al. A Matheuristic Iterative Approach for Profit-Oriented Line Planning Applied to the Chinese High-Speed Railway Network. J. Adv. Transp., 2020. https://doi.org/10.1155/2020/4294195
  25. Wong, R. C., Yuen, T. W., Fung, K. W., & Leung, J. M. Optimizing timetable synchronization for rail mass transit. Transp. Sci., 2008; 42(1): 57-69. https://doi.org/10.1287/trsc.1070.0200
  26. Kaspi, M., & Raviv, T. Service-oriented line planning and timetabling for passenger trains. Transp. Sci., 2013; 47(3): 295-311. https://doi.org/10.1287/trsc.1120.0424
  27. Shuo Zhao;Runfa Wu;Feng Shi; (2021). A line planning approach for high-speed railway network with time-varying demand. Computers & Industrial Engineering. https://doi.org/10.1016/j.cie.2021.107547
  28. Yu-Hern Chang; Chung-Hsing Yeh; Ching-Cheng Shen. A multiobjective model for passenger train services planning: application to Taiwan's high-speed rail line. 2000; 34(2): 0-106. https://doi.org/10.1016/S0191-2615(99)00013-2
  29. Parbo, Jens; Nielsen, Otto A.; Prato, Carlo G. (2018). Reducing passengers' travel time by optimising stopping patterns in a large-scale network: A case-study in the Copenhagen Region. Transportation Research Part A: Policy and Practice, 113: 197-212. https://doi.org/10.1016/j.tra.2018.04.012
  30. Friedrich M, Hartl M, Schiewe A, et al. Integrating Passengers' Assignment in Cost-Optimal Line Planning. In 17th workshop on algorithmic approaches for transportation modelling, optimization, and systems (atmos 2017). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik.
  31. Costa A L, Cunha M D C, Coelho P A et al. Solving high-speed rail planning with the simulated annealing algorithm. J. Transp. Eng., 2013; 139(6): 635-642. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000542
  32. Bangertm P. Optimization: Simulated Annealing. In: Optimization for Industrial Problems. 165-200, Springer, Berlin, Heidelberg, 2012. https://doi.org/10.1007/978-3-642-24974-7_7
  33. Wenqing L, Shaoquan N, Yuhua Y, et al. Research on Passenger Flow Assignment Method of High-speed Railway Based on Line plan. Journal of the China Railway Society. 2021; 43(03): 1-8.
  34. Song P. Optimization Theory and Method for the High Speed Railway Line Planning Based on Dynamic Passenger Demand. 63, Southwest Jiaotong University, 2016. (in Chinese)
  35. Liu J, Schonfeld P M, Zhan S, Du B, He M, Wang K C, & Yin Y. The Economic Value of Reserve Capacity Considering the Reliability and Robustness of a Rail Transit Network. Journal of Transportation Engineering, Part A: Systems, 149(6), 04023046. https://doi.org/10.1061/JTEPBS.TEENG-7691