Skip to main content
Log in

An Optimal Operation Planning Model for High-Speed Rail Transportation

  • Research Paper
  • Published:
International Journal of Civil Engineering Aims and scope Submit manuscript

Abstract

A reasonable train operation plan for railway passenger transportation should jointly optimize the service quality and rail operator’s revenue. This paper synthesizes revenue management and train operation planning to develop an integrated model to maximize the operator’s revenue and minimize passenger’s general cost, which is applied to optimize the rail train frequencies, stopping patterns and seats’ allocation dynamically. An integer program is designed to describe this problem, which is solved by the CVX toolbox. The Chengdu–Chongqing high-speed rail line is applied to demonstrate the effectiveness of the proposed methodology. The optimal frequencies are 95 trains per day, comparing the actual frequencies of 69 trains per day. The total profit increased by 24%, and the passengers’ waiting time reduced greatly. It can be seen that the proposed model is effective for the optimization of the rail planning, which significantly increases the total revenue and reduces the passengers’ waiting time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Anthony RN (1965) Planning and control systems: a framework for analysis. Harvard University, Harvard

    Google Scholar 

  2. Claessens MT, van Dijk NM, Zwaneveld PJ (1998) Cost optimal allocation of rail passenger lines. Eur J Oper Res 110(3):474–489

    Article  MATH  Google Scholar 

  3. Lindner T, Zimmermann UT (2005) Cost optimal periodic train scheduling. Math Methods Oper Res 62(2):281–295

    Article  MathSciNet  MATH  Google Scholar 

  4. Yue Y, Wang S, Zhou L, Tong L, Saat MR (2016) Optimizing train stopping patterns and schedules for high-speed passenger rail corridors. Transp Res C Emerg Technol 63:126–146

    Article  Google Scholar 

  5. Zhou W, Shi F, Chen Y, Deng L (2011) Method of integrated optimization of train operation plan and diagram for network of dedicated passenger lines. J China Railway Soc 33(2):1–7

    Google Scholar 

  6. Goossens JW, van Hoesel S, Kroon L (2004) A branch-and-cut approach for solving railway line-planning problems. Transp Sci 38(3):379–393

    Article  Google Scholar 

  7. Goossens JW, van Hoesel S, Kroon L (2006) On solving multi-type railway line planning problems. Eur J Oper Res 168(2):403–424

    Article  MathSciNet  MATH  Google Scholar 

  8. Bussieck MR, Lindner T, Lübbecke ME (2004) A fast algorithm for near cost optimal line plans. Math Methods Oper Res 59(2):205–220

    Article  MathSciNet  MATH  Google Scholar 

  9. Torres LM, Torres R, Borndoerfer R, Pfetsch ME (2011) Line planning on tree networks with applications to the Quito Trolebus system. Int Trans Oper Res 18(4):455–472

    Article  MathSciNet  MATH  Google Scholar 

  10. Torres LM, Torres R, Borndörfer R, Pfetsch ME (2008) On the line planning problem in tree networks. Konrad-Zuse-Zentrum für Informationstechnik Berlin, Berlin

    MATH  Google Scholar 

  11. Bussieck MR, Kreuzer P, Zimmermann UT (1997) Optimal lines for railway systems. Eur J Oper Res 96(1):54–63

    Article  MATH  Google Scholar 

  12. Pierick K, Wiegand K (1976) Methodical formulations for an optimization of railway long distance passenger transport. Rail Int 7(6):328–340

    Google Scholar 

  13. Bussieck M (1998) Optimal lines in public rail transport. Braunschweig Technology University, Braunschweig

    Google Scholar 

  14. Li D, Ding S, Wang Y (2018) Combinatorial optimization of service order and overtaking for demand-oriented timetabling in a single railway line. J Adv Transp 2018:1–21

    Google Scholar 

  15. Wang Y, Tang T, Ning B, van den Boom TJJ, De Schutter B (2015) Passenger-demands-oriented train scheduling for an urban rail transit network. Transp Res C Emerg Technol 60:1–23

    Article  Google Scholar 

  16. Yin J, Yang L, Tang T, Gao Z, Ran B (2017) Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches. Transp Res B Methodol 97:182–213

    Article  Google Scholar 

  17. Schöbel A, Scholl S (2006) Line planning with minimal traveling time. ATMOS, Dallas

    MATH  Google Scholar 

  18. Barrena E, Canca D, Coelho LC, Laporte G (2014) Exact formulations and algorithm for the train timetabling problem with dynamic demand. Comput Oper Res 44(3):66–74

    Article  MathSciNet  MATH  Google Scholar 

  19. Niu H, Tian X, Zhou X (2015) Demand-driven train schedule synchronization for high-speed rail lines. IEEE Trans Intell Transp Syst 16(5):2642–2652

    Article  Google Scholar 

  20. Niu H, Zhou X, Gao R (2015) Train scheduling for minimizing passenger waiting time with time-dependent demand and skip-stop patterns: Nonlinear integer programming models with linear constraints. Transp Res B Methodol 76:117–135

    Article  Google Scholar 

  21. Ingvardson JB, Nielsen OA, Raveau S, Nielsen BF (2018) Passenger arrival and waiting time distributions dependent on train service frequency and station characteristics: a smart card data analysis. Transp Res C Emerg Technol 90:292–306

    Article  Google Scholar 

  22. Shi J, Yang L, Yang J, Gao Z (2018) Service-oriented train timetabling with collaborative passenger flow control on an oversaturated metro line: an integer linear optimization approach. Transp Res B Methodol 110:26–59

    Article  Google Scholar 

  23. Borndörfer R, Grötschel M, Pfetsch ME (2007) A column-generation approach to line planning in public transport. Transp Sci 41(1):123–132

    Article  Google Scholar 

  24. Feng SH, I. D, Lianbo, Liang HUO (2007) i-Level programming model and algorithm of passenger train operation plan. China Railway Sci 28(3):110–116

    Google Scholar 

  25. Jong JC, Chang S, Lai YC (2013) Development of a two-stage hybrid method for solving high speed rail train scheduling problem. Transp Res Rec 2374:44–54

    Article  Google Scholar 

  26. Crevier B, Cordeau J-F, Savard G (2012) Integrated operations planning and revenue management for rail freight transportation. Transp Res B Methodol 46(1):100–119

    Article  Google Scholar 

  27. Wang Y, Schutter BD, Boom TJJVD, Ning B (2013) Optimal trajectory planning for trains—a pseudospectral method and a mixed integer linear programming approach. Transp Res C 29(29):97–114

    Article  Google Scholar 

  28. Chang YH, Yeh CH, Shen CC (2000) A multiobjective model for passenger train services planning: application to Taiwan’s high-speed rail line. Transp Res Part B 34(2):91–106

    Article  Google Scholar 

  29. Jong JC, Suen CS, Chang SK (2012) A decision support system to optimize railway stopping patterns: application to the Taiwan high speed rail. Transp Res Rec 2289:24–33

    Article  Google Scholar 

  30. Wang Y, Tang T, Ning B, Meng L (2017) Integrated optimization of regular train schedule and train circulation plan for urban rail transit lines. Transp Res E Logist Transp Rev 105:83–104

    Article  Google Scholar 

  31. Alptekin GI (2015) Strategic pricing model based on genetic algorithm: the case of electronic publishing market. Journal of Intelligent Fuzzy Systems 29(4):1551–1564

    Article  Google Scholar 

  32. Khamseh AA, Soleimani F, Naderi B (2014) Pricing decisions for complementary products with firm’s different market powers in fuzzy environments. J Intell Fuzzy Syst 27(5):2327–2340

    MathSciNet  MATH  Google Scholar 

  33. Sang S (2014) Optimal models in price competition supply chain under a fuzzy decision environment. J Int Fuzzy Syst 27(1):257–271

    MathSciNet  MATH  Google Scholar 

  34. Ciliberto F, Watkins E, Williams JW (2017) Collusive Pricing Patterns in the US Airline Industry. Social Science Electronic Publishing, Waltham

    Google Scholar 

  35. Escobari D, Jindapon P (2014) Price discrimination through refund contracts in airlines. Int J Ind Organ 34(1):1–8

    Article  Google Scholar 

  36. Richards TJ, Liaukonyte J, Streletskaya NA (2016) Personalized pricing and price fairness. Int J Ind Organ 44:138–153

    Article  Google Scholar 

  37. Lemus AB, Moreno D (2017) Price caps with capacity precommitment. Int J Ind Organ 50:131–158

    Article  Google Scholar 

  38. Constantinou E, Bernhardt D (2018) The price-matching dilemma. Int J Ind Organ 59:97–113

    Article  Google Scholar 

  39. Luttmann A (2018) Evidence of directional price discrimination in the U.S. Airline Industry. Int J Ind Organ 62:291–329

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Social Science Foundation of China under Grant 14BGL060.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaoqiang Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, X., Li, L. & Afzal, M. An Optimal Operation Planning Model for High-Speed Rail Transportation. Int J Civ Eng 17, 1397–1407 (2019). https://doi.org/10.1007/s40999-019-00401-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40999-019-00401-w

Keywords

Navigation