Abstract
Optimizing stop plans of train lines greatly contributes to improving the quality of rail passenger service. Traditionally, stop plans are pre-specified according to the classification of stations in the line planning process. However, with the expansion of railway networks and the great changes of travel demand among different origin–destination pairs (ODs), it becomes more difficult to generate stops using this simple method. To meet the new challenges of line planning in railway management, a linear integer programming model based on a new definition of lines is presented in this paper. In the proposed model, proper lines with reasonable train ODs and frequencies can be selected from a series of potential lines in the given line pool. The stops of selected lines can be chosen from candidate stop sets that are generated based on both station classification and types of trains. More practical considerations of stop planning are integrally considered, i.e., the balance of the stop distribution and restrictions on the stop numbers. In experiments involving small-scale cases, the stop numbers decrease under different types of demand scenarios when using the proposed method compared to the traditional methods. We also conduct a series of sensitivity analyses using large-scale random cases to reveal the impact of different stopping rules on the quality of passenger services. Finally, two real-world case studies based on the Beijing-Shanghai high-speed rail network are utilized to demonstrate the applicability of the proposed method.
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References
Borndörfer R, Grötschel M, Pfetsch ME (2007) A column-generation approach to line planning in public transport [J]. Transp Sci 41(1):123–132
Bull SH, Lusby RM, Larsen J (2015) An optimization based method for line planning to minimize travel time[C]//13th Conference on Advanced Systems in Public Transport. DTU Management Engineering, Erasmus University
Bussieck MR, Lindner T, Lübbecke ME (2004) A fast algorithm for near cost optimal line plans [J]. Math Methods Oper Res 59(2):205–220
Chang YH, Yeh CH, Shen CC (2000) A multiobjective model for passenger train services planning: application to Taiwan's high-speed rail line [J]. Transp Res B Methodol 34(2):91–106
Chen D, Ni S, Xu C et al (2016) High-speed train stop-schedule optimization based on passenger travel convenience [J]. Math Probl Eng 2016:1
Deng L, Shi F, Zhou W (2009) Stop schedule plan optimization for passenger train [J]. China Railw Sci 30(4):102–107
Fu H, Nie L, Yang H et al (2012) Research on the method for optimization of candidate-train-set based train operation plans for high-speed railways [J]. J China Railw Soc 32(6):1–8
Fu H, Nie L, Meng L et al (2015) A hierarchical line planning approach for a large-scale high speed rail network: the China case [J]. Transp Res A Policy Pract 75:61–83
Gattermann P, Harbering J, Schöbel A (2017) Line pool generation [J]. Public Transp 9(1–2):7–32
Goerigk M, Schachtebeck M, Schöbel A (2013) Evaluating line concepts using travel times and robustness [J]. Public Transp 5(3):267–284
Goossens JW, van Hoesel S, Kroon L (2006) On solving multi-type railway line planning problems [J]. Eur J Oper Res 168(2):403–424
Harbering J (2017) Delay resistant line planning with a view towards passenger transfers [J]. TOP 25(3):467–496
Jamili A, Aghaee MP (2015) Robust stop-skipping patterns in urban railway operations under traffic alteration situation [J]. Transp Res Part C: Emerg Technol 61:63–74
Jiang F, Cacchiani V, Toth P (2017) Train timetabling by skip-stop planning in highly congested lines [J]. Transp Res B Methodol 104:149–174
Jong JC, Suen CS, Chang S (2012) Decision support system to optimize railway stopping patterns: application to Taiwan high-speed rail [J]. Transp Res Rec: J Transp Res Board 2289:24–33
Khani A, Hickman M, Noh H (2015) Trip-based path algorithms using the transit network hierarchy [J]. Netw Spat Econ 15(3):635–653
Lai Y, Shih M, Chen G et al (2016) Development of efficient stop planning optimization process for high-speed rail systems [J]. J Adv Transp 50(8):1802–1819
Larrain H, Munoz JC (2008) Public transit corridor assignment assuming congestion due to passenger boarding and alighting [J]. Netw Spat Econ 8(2–3):241–256
Lee YJ, Shariat S, Choi K (2014) Optimizing skip-stop rail transit stopping strategy using a genetic algorithm [J]. J Public Transp 17(2):7
Li D, Han B, Li X et al (2013) High-speed railway stopping schedule optimization model based on node service [J]. J China Railw Soc 35:1–5
Lin DY, Ku YH (2014) An implicit enumeration algorithm for the passenger service planning problem: application to the Taiwan railways administration line [J]. Eur J Oper Res 238(3):863–875
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 [J]. Transp Res B Methodol 76:117–135
Niu F, Qi JG, Qin J (2016) Optimization model for train stopping plan on high-speed railway corridor with uncertain passenger demands [J]. J China Railw Soc 38(7):1–7
Okada K, Miyashiro R (2012) Optimization of assignment of rapid train stops: example of the JR Nambu line [J]. J Adv Mech Des Syst Manuf 6(5):622–632
Parbo J, Nielsen O A, Prato C G 2015. Adapting stopping patterns in complex railway networks to reduce passengers’ travel time [C]. 6th International conference on railway operations modelling and analysis – Rail Tokyo 2015, Tokyo, Japan
Park BH, Seo YI, Hong SP et al (2013) Column generation approach to line planning with various halting patterns – application to the Korean high-speed railway [J]. Asia Pac J Oper Res 30(04):1350006
Qi J, Li S, Gao Y et al (2017) Joint optimization model for train scheduling and train stop planning with passengers distribution on railway corridors [J]. J Oper Res Soc:1–16
Qi J, Yang L, Di Z et al (2018) Integrated optimization for train operation zone and stop plan with passenger distributions [J]. Transp Res Part E: Logist Transp Rev 109:151–173
Schöbel, A (2012) Line planning in public transportation: models and methods[J]. Or Spectrum 34(3):491–510
Schöbel A, Schwarze S (2006) A game-theoretic approach to line planning[C]// 6th Workshop on Algorithmic Methods and Models for Optimization of Railways (ATMOS'06). (https://doi.org/10.4230/OASIcs.ATMOS.2006.688)
Scholl S. 2005 Customer-oriented line planning [M]. Dissertation. de
Sogin SL, Caughron BM, Chadwick SG (2012) Optimizing skip stop service in passenger rail transportation [C]//2012 Joint Rail Conference. American Society of Mechanical Engineers, New York, pp 501–512
Ulusoy Y, Chien S, Wei CH (2010) Optimal all-stop, short-turn, and express transit services under heterogeneous demand [J]. Transp Res Rec: J Transp Res Board 2197:8–18
Yamauchi T, Takamatsu M, Imahori S, et al. 2017 Optimizing train stopping patterns for congestion management [C]. Algorithmic Approaches for Transportation Modeling, Optimization, and Systems
Yang L, Qi J, Li S, Gao Y (2016) Collaborative optimization for train scheduling and train stop planning on high-speed railways [J]. Omega 64:57–76
Yue Y, Wang S, Zhou L, Tong L, Saat MR (2016) Optimizing train stopping patterns and schedules for high-speed passenger rail corridors [J]. Transp Res Part C: Emerg Technol 63:126–146
Zhang X, Nie L (2016) Integrating capacity analysis with high-speed railway timetabling: a minimum cycle time calculation model with flexible overtaking constraints and intelligent enumeration [J]. Transp Res Part C: Emerg Technol 68:509–531
Zhang X, Nie L (2017) Railway capacity analysis based on train time window by utilizing macroscopic cyclic timetabling model. 8th International Conference on Railway Operations Modelling and Analysis, ICROMA. Presentation, Lille
Zhu Y, Goverde RMP (2019) Dynamic passenger assignment for major railway disruptions considering information interventions [J]. Netw Spat Econ 19:1249–1279
Acknowledgments
This work was supported by the Ministry of Science and Technology of China [No. 2016YFE0201700] and the National Natural Science Foundation of China [No. U1934216], [No. 61703030].
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Zhang, X., Nie, L., Wu, X. et al. How to Optimize Train Stops under Diverse Passenger Demand: a New Line Planning Method for Large-Scale High-Speed Rail Networks. Netw Spat Econ 20, 963–988 (2020). https://doi.org/10.1007/s11067-020-09506-5
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DOI: https://doi.org/10.1007/s11067-020-09506-5