A Combined Simulation-Optimization Approach for Robust Timetabling on Main Railway Lines

References

• Ait Ali A, Eliasson J (2022) European railway deregulation: An overview of market organization and capacity allocation. Transportmetrica A Transport Sci. 18(3):594–618.Crossref, Google Scholar
• Andersson EV, Peterson A, Törnquist Krasemann J (2013) Quantifying railway timetable robustness in critical points. J. Rail Transport Planning Management 3(3):95–110.Crossref, Google Scholar
• Andersson EV, Peterson A, Törnquist Krasemann J (2015) Reduced railway traffic delays using a MILP approach to increase robustness in critical points. J. Rail Transport Planning Management 5(3):110–127.Crossref, Google Scholar
• Batley R, Ibáñez JN (2012) Randomness in preference orderings, outcomes and attribute tastes: An application to journey time risk. J. Choice Model. 5(3):157–175.Crossref, Google Scholar
• Bešinović N, Goverde RM, Quaglietta E, Roberti R (2016) An integrated micro-macro approach to robust railway timetabling. Transportation Res. Part B Methodological 87:14–32.Crossref, Google Scholar
• Brännlund U, Lindberg PO, Nõu A, Nilsson JE (1998) Railway timetabling using Lagrangian relaxation. Transportation Sci. 32(4):358–369.Link, Google Scholar
• Burggraeve S, Vansteenwegen P (2017) Optimization of supplements and buffer times in passenger robust timetabling. J. Rail Transport Planning Management 7(3):171–186.Crossref, Google Scholar
• Cacchiani V, Toth P (2012) Nominal and robust train timetabling problems. Eur. J. Oper. Res. 219(3):727–737.Crossref, Google Scholar
• Cacchiani V, Caprara A, Fischetti M (2012) A Lagrangian heuristic for robustness, with an application to train timetabling. Transportation Sci. 46(1):124–133.Link, Google Scholar
• Caimi G, Kroon L, Liebchen C (2017) Models for railway timetable optimization: Applicability and applications in practice. J. Rail Transport Planning Management 6(4):285–312.Crossref, Google Scholar
• Caprara A, Fischetti M, Toth P (2002) Modeling and solving the train timetabling problem. Oper. Res. 50(5):851–861.Link, Google Scholar
• Carrion C, Levinson D (2012) Value of travel time reliability: A review of current evidence. Transportation Res. Part A Policy Pract. 46(4):720–741.Crossref, Google Scholar
• Chen DS, Batson RG, Dang Y (2010) Applied Integer Programming: Modeling and Solution (John Wiley & Sons, Hoboken, NJ).Google Scholar
• Chow AH, Pavlides A (2018) Cost functions and multi-objective timetabling of mixed train services. Transportation Res. Part A Policy Pract. 113:335–356.Crossref, Google Scholar
• Dewilde T, Sels P, Cattrysse D, Vansteenwegen P (2014) Improving the robustness in railway station areas. Eur. J. Oper. Res. 235(1):276–286.Crossref, Google Scholar
• Ferreira L, Higgins A (1996) Modeling reliability of train arrival times. J. Transportation Engrg. 122(6):414–420.Crossref, Google Scholar
• Fischetti M, Monaci M (2009) Light robustness. Ahuja RK, Möhring RH, Zaroliagis CD, eds. Robust and Online Large-Scale Optimization, Lecture Notes in Computer Science, vol. 5868 (Springer, Berlin), 61–84.Crossref, Google Scholar
• Fischetti M, Salvagnin D, Zanette A (2009) Fast approaches to improve the robustness of a railway timetable. Transportation Sci. 43(3):321–335.Link, Google Scholar
• Goverde RMP, Hansen IA (2013) Performance indicators for railway timetables. 2013 IEEE Internat. Conf. Intelligent Rail Transportation Proc., 301–306. https://ieeexplore.ieee.org/xpl/conhome/6684703/proceeding.Google Scholar
• Harrod SS (2012) A tutorial on fundamental model structures for railway timetable optimization. Surveys Oper. Res. Management Sci. 17(2):85–96.Crossref, Google Scholar
• Herrigel S, Laumanns M, Szabo J, Weidmann U (2018) Periodic railway timetabling with sequential decomposition in the PESP model. J. Rail Transport Planning Management 8(3):167–183.Crossref, Google Scholar
• Higgins A, Kozan E (1998) Modeling train delays in urban networks. Transportation Sci. 32(4):346–357.Link, Google Scholar
• Higgins A, Kozan E, Ferreira L (1996) Optimal scheduling of trains on a single line track. Transportation Res. Part B Methodological 30(2):147–161.Crossref, Google Scholar
• Högdahl J (2019a) A simulation-optimization approach for improved robustness of railway timetables. Licentiate thesis, Kungliga Tekniska högskolan, Stockholm.Google Scholar
• Högdahl J (2019b) Delay prediction with flexible train order in a MILP simulation-optimization approach for railway timetabling. Proc. 8th Internat. Conf. Railway Oper. Model. Anal. RailNorrköping.Google Scholar
• Högdahl J, Bohlin M, Fröidh O (2017) Combining optimization and simulation to improve railway timetable robustness. Proc. 7th Internat. Conf. Railway Oper. Model. Anal. RailLille.Google Scholar
• Högdahl J, Bohlin M, Fröidh O (2019) A combined simulation-optimization approach for minimizing travel time and delays in railway timetables. Transportation Res. Part B Methodological 126:192–212.Crossref, Google Scholar
• Hyndman RJ, Koehler AB (2006) Another look at measures of forecast accuracy. Internat. J. Forecasting 22(4):679–688.Crossref, Google Scholar
• Jovanovic D, Harker PT (1991) Tactical scheduling of rail operations. The SCAN I system. Transportation Sci. 25(1):46–64.Link, Google Scholar
• Kroon L, Maróti G, Helmrich MR, Vromans M, Dekker R (2008) Stochastic improvement of cyclic railway timetables. Transportation Res. Part B Methodological 42(6):553–570.Crossref, Google Scholar
• Kroon L, Huisman D, Abbink E, Fioole PJ, Fischetti M, Maróti G, Schrijver A, Steenbeek A, Ybema R (2009) The new Dutch timetable: The OR revolution. Interfaces 39(1):6–17.Link, Google Scholar
• Kruskal WH, Wallis WA (1952) Use of ranks in one-criterion variance analysis. J. Amer. Statist. Assoc. 47(260):583–621.Crossref, Google Scholar
• Lamorgese L, Mannino C, Natvig E (2017) An exact micro-macro approach to cyclic and non-cyclic train timetabling. Omega 72:59–70.Crossref, Google Scholar
• Lee Y, Lu LS, Wu ML, Lin DY (2017) Balance of efficiency and robustness in passenger railway timetables. Transportation Res. Part B Methodological 97:142–156.Crossref, Google Scholar
• Liebchen C (2008) The first optimized railway timetable in practice. Transportation Sci. 42(4):420–435.Link, Google Scholar
• Liebchen C, Lübbecke M, Möhring R, Stiller S (2009) The concept of recoverable robustness, linear programming recovery, and railway applications. Ahuja RK, Möhring RH, Zaroliagis CD, eds. Robust and Online Large-Scale Optimization, Lecture Notes in Computer Science, vol. 5868 (Springer, Berlin), 1–27.Crossref, Google Scholar
• Liebchen C, Schachtebeck M, Schöbel A, Stiller S, Prigge A (2010) Computing delay resistant railway timetables. Comput. Oper. Res. 37(5):857–868.Crossref, Google Scholar
• Nelldal BL, Lindfeldt O, Sipilä H, Wolfmaier J (2008) Improved punctuality for X2000: Analyzed using simulation. Report, Kungliga Tekniska Högskolan, Stockholm.Google Scholar
• Palmqvist CW, Olsson N, Hiselius L (2017) Some influencing factors for passenger train punctuality in Sweden. Internat. J. Prognostics Health Management 8(3):1–13.Google Scholar
• Palmqvist CW, Olsson NO, Winslott Hiselius L (2018) The planners’ perspective on train timetable errors in Sweden. J Adv. Transportation 2018:58502819.Google Scholar
• Polinder GJ, Breugem T, Dollevoet T, Maróti G (2019) An adjustable robust optimization approach for periodic timetabling. Transportation Res. Part B Methodological 128:50–68.Crossref, Google Scholar
• Radtke A, Hauptmann D (2004) Automated planning of timetables in large railway networks using a microscopic data basis and railway simulation techniques. Allan J, Brebbia CA, Hill RJ, Sciutto G, Sone S, eds. Computers in Railways IX (WIT Press, Southampton, United Kingdom), 615–625.Google Scholar
• Rosberg T, Thorslund B (2020) Simulated and real train driving in a lineside automatic train protection (ATP) system environment. J. Rail Transport Planning Management 16:1.Crossref, Google Scholar
• Schlechte T, Borndörfer R (2010) Balancing efficiency and robustness: A bi-criteria optimization approach to railway track allocation. Ehrgott M, Naujoks B, Stewart TJ, Wallenius J, eds. Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems, Lecture Notes in Economics and Mathematical Systems, vol. 634 (Springer, Berlin), 105–116.Crossref, Google Scholar
• Schöbel A, Kratz A (2009) A bicriteria approach for robust timetabling. Ahuja RK, Möhring RH, Zaroliagis CD, eds. Robust and Online Large-Scale Optimization, Lecture Notes in Computer Science, vol. 5868, (Springer, Berlin), 119–144.Crossref, Google Scholar
• Sels P, Dewilde T, Cattrysse D, Vansteenwegen P (2016) Reducing the passenger travel time in practice by the automated construction of a robust railway timetable. Transportation Res. Part B Methodological 84:124–156.Crossref, Google Scholar
• Serafini P, Ukovich W (1989) A mathematical model for periodic scheduling problems. SIAM J. Discrete Math. 2(4):550–581.Crossref, Google Scholar
• Solinen E, Nicholson G, Peterson A (2017) A microscopic evaluation of railway timetable robustness and critical points. J. Rail Transport Planning Management 7(4):207–223.Crossref, Google Scholar
• Szpigel B (1973) Optimal train scheduling on a single track railway. Ross M, ed. Oper. Res. ’72: Proc. Sixth IFORS Internat. Conf. Oper. Res. (North-Holland Publishing Company, Amsterdam), 343–352.Google Scholar
• Trafikverket (2014) Guidelines for train density: Planning prerequisites: Train plan T15. Report, Trafikverket, Borlänge, Sweden.Google Scholar
• Trafikverket (2020) Method of analysis and socio-economic calculation values for the transport sector: ASEK 7.0. Report, Trafikverket, Borlänge, Sweden.Google Scholar
• Trafikverket (2021a) Analysis of designated deficiencies at the Swedish Western Main Line: Background for the revision of the National Plan 2018–2029. Report, Trafikverket, Borlänge, Sweden.Google Scholar
• Trafikverket (2021b) Network statement 2023. Report, Trafikverket, Borlänge, Sweden.Google Scholar
• Warg J, Bohlin M (2016) The use of railway simulation as an input to economic assessment of timetables. J. Rail Transport Planning Management 6(3):255–270.Crossref, Google Scholar
• Yan F, Bešinović N, Goverde RM (2019) Multi-objective periodic railway timetabling on dense heterogeneous railway corridors. Transportation Res. Part B Methodological 125:52–75.Crossref, Google Scholar